VOLUME 12, ISSUE 4, APRIL 2023

Abstract: In the discipline of pattern recognition, optical character recognition is a critical task. Many academics have researched English character recognition extensively, however, in the case of Indian characters, there has been less investigation. Languages that are difficult to understand, extensive research required. Devanagari is a commonly used Indian script. Individuals from India Devanagari is the foundation for a number of languages. Hindi, Sanskrit, Kashmiri, and Marathi are among the Indian languages and so forth. A review of previous studies is presented in this article. Work on Devanagari character recognition as well as a few uses for an optical character recognition system. Character recognition is a research problem that has been ongoing for many years. In optical character recognition, a procedure of automatically recognizing the optically scanned character images and digitized character images is to be developed into an electronic text document. Devanagari is an Indian script that is a very popular script among millions of people. There are many Indian languages that are the basis of Devanagari. Those languages are Hindi, Sanskrit, Kashmiri, Marathi, and many more. English character recognition is mostly studied by researchers and a lot of commercial systems are used for it. But for Indian languages, the research work is very limited because of the complex formation of the language.

Keywords: Include at least 4 keywords or phrases.

Abstract: This research paper delves into the world of luggage tracking, presenting a highly innovative system that utilizes the powerful technologies of IoT, GSM, and GPS components. Through this system, luggage can be accurately tracked in real-time, delivering highly precise location-based information to the user. The system's architecturally advanced design features an intricate combination of components, including a microcontroller, GPS module, GSM module, and IoT platform, all working together in unison to produce an incredibly efficient and reliable system. The microcontroller, a highly advanced component at the heart of this system, plays a critical role in processing GPS data, which is then sent to the IoT platform using the impressive GSM module. Once the platform receives the data, it processes it with an incredible level of precision, displaying a geographical depiction of the position of the luggage. The system's broad range of potential applications is truly awe-inspiring, with its usefulness extending to luggage tracking for airports, hotels, and transportation companies, to name but a few. This comprehensive study highlights the power and effectiveness of integrating IoT, GSM, and GPS technologies into a single cohesive system, opening up vast new possibilities for future research in this captivating field.

Keywords: GPS luggage tracking, GSM, Internet of Things, IOT, Wireless luggage tracking

Abstract: The safety of miners in the mining environment is a major challenge. A miner's health and life are exposed to many critical issues. Underground mining requires continuous monitoring of every parameter like methane gas, high temperature, fire accidents monitored. Disasters in coal mines are due to the complexity of the mining environment and the various tasks carried out in coal mines. So, it is very important to monitor the working environment of coal mines. Coal mine monitoring systems are wired network systems that play an important role in the safe production of coal mines. Due to the continuous expansion and deepening of the exploitation areas of coal mines, many paths are turning into blind areas, which have a lot of hidden dangers. To overcome this problem, advanced mechanisms have been proposed in a coal mine safety monitoring system that can improve the monitoring level of production safety and reduce accidents in coal mines.

Keywords: Gas sensor, MEMS sensor, LDR sensor, Buzzer

Abstract: A thrift store is not like a regular retail store for shopping. You don't always go to a secondhand store with a list when you do. Instead, then focusing on finding a specific item, thrift shopping is more about the hunt. It's fascinating to see what you could find in a thrift store because they are stocked with old and out-of-season items. You buy whatever appeals to you and that you adore! Additionally, you'll see that your bill is substantially less expensive than it would be at a retail store when you reach the checkout line. It's fun to imagine what you could find when you browse in a thrift store. Most individuals go thrift store shopping for the excitement of the search. The majority of people who shop at thrift stores are also artists. They have the imagination to see a new application for a gently used object. For instance, clothing in a thrift shop may not always be in-season, but consumers who purchase items there might become creative to express their own personal style in a way that is appropriate for the current season. Thrifting is a web-based application that provides a platform for buying and selling second-hand items such as clothing, fashion essentials. The purpose of this market survey is to understand the needs and preferences of potential users and to assess the demand for such a service.  

Keywords: Second-hand, Thrift store, Thrifting, Market survey.

Abstract: A smart health system that benefits both patients and doctors is a personal health record (PHR) system. Typically, a PHR is managed and kept on the cloud by a semi-reliable cloud service provider. Nonetheless, there is still a chance that untrusted people and semi trusted parties could see confidential health information. In this article, a patient-centric PHR sharing structure is suggested in order to safeguard patients' privacy and guarantee that they have control over their PHRs. This framework eliminates the key hosting issue and achieves fine-grained access control to PHRs by encrypting all PHRs with multiauthority attribute-based encryption prior to outsourcing. In order to guarantee data integrity on the cloud and protect the user's identity during authentication, an anonymous authentication between the cloud and the user is also suggested. The new online-offline attribute-based signature that the proposed authentication is based on is issued. It can strengthen patients' control over their PHRs by making the encrypted PHRs resistant to collusion attempts and preventing forgery during the sharing time. Decryption that is done online-offline and through outsourcing also lowers computation costs and boosts productivity. Lastly, comparisons based on numerical trials are shown.

Keywords: Process discovery; hybrid process model; event log; big data; service computing; cloud computing

Abstract: Banking institutions have essentially become the only source of confidence for online commerce in order to carry out electronic payments. With a peer-to-peer electronic cash system, payments might be performed online directly between parties without going through a banking institution. But, if a trustworthy third party is still required to prevent double spending, the main benefits of digital signatures are lost. So, using block chain technology to construct hash functions, we may implement a Bit Coin-based financial system in this project. Bit coin is a form of digital currency that is not supported by the central bank or government of any nation. The building blocks of safe data are these bit coins. In order to safely validate each transaction, it is necessary to send this data from one person to another while also verifying the transaction with money. The P2P network tracks and validates the exchange of digital currency between users. Bit coin is more secure than other currencies in terms of cryptographic implementation, and it is difficult to carry out fraudulent transactions. In a Bit coin transaction, the block chain will connect all users connected to the network, and each time a transaction is entered, the network will broadcast it to other users after it has been validated. The network will also have a copy of every transaction. The network will group transaction data into blocks and broadcast them throughout the network rather than preserving any transactions in the block chain. Every single block in this chain links to the one before it, and the genesis block is the first block in the chain. Since peer-to-peer networks and a consensus mechanism are used in block chain systems, there is no chance of data alteration.

Keywords: Blockchain Technology, Transparency, Reshaping the future of Banking, Decentralization.

Abstract: The proposed driver fatigue and accident-avoidance system has aim to reduce the risk of accidents caused by the driver fatigue by integrating a monitoring software and warning alarm in vehicles. The system uses haar cascade classifiers to monitor the driver eye, mouth opening and head movement will be detected using haar cascade classifers which focus on the region of interests. Haar cascade classifier classifies the driver drowsiness level and create an alert based on that.  A machine learning algorithm classify the drivers drowsiness level as an alert once the system detects the drivers drowsiness level has exceeded a pre-defined threshold it will activates the warning system that can include visual, audito to prompt the driver to take the action. For instance, the warning system may issue an audible alert or vibrate the steering wheel to alert the driver. The proposed system can improve driver safety and lower the number of accidents caused by driver fatigue by providing a real-time warning system to alert drivers to their drowsiness level, helping them to take corrective action and avoid accidents. Furthermore, the system can be tailored to different driving conditions and integrated into various types of vehicles.

Keywords: ordering food, notifying the expiry date

Abstract: Over decades, agriculture has seen tremendous revolution. The development of farm machineries such as tractors, harvesters, improved irrigation systems have contributed immensely to food security and sustainable economy. The development of Computers has contributed significantly in improving our daily activities, and agriculture is not an exception. New technology called Internet of Things (IoT) is bringing to light amazing developments in process automation, process control, data collection, and real-time response to events. It has helped in home automation, self-driving cars, Unmanned Aerial vehicles and many more. IoT can be applied in agriculture by means of sensors aimed at field monitoring, disease detection; temperature, humidity and soil moisture monitoring, automatic irrigation system, IoT based drones, farm animals monitoring etc. The change of climate in the Sahel, caused largely by global warming and desertification, has affected so much of production and farm output, we aim in this research to apply IoT technology in climate monitoring such as the temperature and humidity, soil moisture monitoring, crop management, precision farming practice, , farm management using End-to-End Farm Management System. The result shows an interesting output of the variations in temperature, humidity, soil moisture, sunlight levels and probable rain drops in the experiment site. The result were shown directly on the LCD screen attached to the Arduino microcontroller and at the same time transmitted over the internet to the IoT cloud and displayed on the Arduino IoT remote application. This research was implemented on a small part on an irrigation site and can thus be expanded to accommodate larger components for use on large farm site.

Keywords: Internet-of-things (IoT), Sensors, Cloud, Irrigation and Farming, Arduino

Abstract: This paper presents an investigation, involving experiments, which shows that current network intrusion, detection, and prevention systems (NIDPSs) have several shortcomings in detecting or preventing rising unwanted traffic and have several threats in high-speed environments. Precise organization traffic recognizable proof is a significant reason for network traffic checking and information investigation, and is the way to work on the nature of client administration. In this paper, through the examination of two organization traffic ID strategies in light of machine learning and profound parcel review, an organization traffic distinguishing proof strategy in view of machine learning and profound bundle examination is proposed. This strategy utilizes profound parcel assessment innovation to distinguish most organization traffic, diminishes the responsibility that should be recognized by machine learning. This paper presents an investigation, involving experiments, which shows that current network intrusion, detection, and prevention systems (NIDPSs) have several shortcomings in detecting or preventing rising unwanted traffic and have several threats in high-speed environments. It shows that the NIDPS performance can be weak in the face of high-speed and high-load malicious traffic in terms of packet drops, outstanding packets without analysis, and failing to detect/prevent unwanted traffic. A novel quality of service (QoS) architecture has been designed to increase the intrusion detection and prevention performance. Our exploration has proposed and assessed an answer involving an original QoS setup in a multi-facet change to sort out parcels/traffic and equal procedures to build the bundle handling speed. The new engineering was tried under various traffic velocities, types, and errands. The trial results show that the design works on the organization and security execution which is can conceal to 8 Gb/s with 0 bundles dropped. This paper likewise shows that this number (8Gb/s) can be improved, yet it relies upon the framework limit which is constantly restricted.

Keywords: Intrusion detection, traffic identification, MDIP, network security, open source, quality of service, security

Abstract: This paper provides a survey of recent research on the detection of fake online reviews using machine learning (ML) techniques. The rise of fake online reviews poses a significant challenge to the credibility of online review platforms, and detecting fake reviews is critical to ensure the integrity of these platforms. The paper reviews different ML techniques, including supervised and unsupervised learning algorithms, hybrid approaches, and deep learning techniques, that have been used to detect fake online reviews. The review highlights the potential of these techniques and emphasizes the need for more robust and accurate models to combat the problem of fake reviews. Overall, the paper provides valuable insights into the ongoing research area of fake review detection using ML techniques.

Abstract: In recent years, there has been a growing demand for secure and efficient voting systems. In this paper, we propose an efficient smart voting system that incorporates facial recognition technology for voter identification. The proposed system uses a combination of user ID verification, voter card number verification, and facial recognition to ensure the integrity of the voting process. We also present a survey of various facial recognition algorithms and their applications in secure voting systems. Our proposed system aims to provide a secure and efficient voting process that can be implemented in various settings, including remote voting and in-person voting.

Keywords: Facial recognition, Smart voting system, Secure voting, Biometric technology, User identification, Voter verification.

Abstract: Presently, people have come to the stage where they feel that it is impossible to live without a mobile phone. It has become a necessary part of their life. Due to this, mobile applications which are useful in day to day lives are in demand. We have a mobile application for every single thing. Therefore, we propose the architecture of a mobile application which acts as a guide for the tourists when they are visiting any unknown place in Karnataka. This model will be for travellers who wish to travel in many areas of Karnataka. Unlike the other apps, the business will offer the utmost coverage of many areas. The speciality of this application is, it does not require internet connection. The application shows the history of the particular place as soon as you enter the name of the place with the location and also one of the advantages is, it will show the nearest hotels for refreshment and lodging. We also have done a market analysis, competitive analysis and future enhancements to the application.

Keywords: Android tourist guide, GPS, GIS

Abstract: Analog to Digital Converter (ADC) is a most useful devices for extracting the digital signals from the analog signals. The processing speed of successive approximation type ADC is depending highly on the operations of the comparators, which is the important parts of structure. In day todays digital ultratech world, low power consumption & speed are the major factor that need to be considered. High speed comparator is much affective to the overall performance of ADC. In order to design a better comparator that will function optimally in real environments without changing its characteristic. Factors like propagation delay, power dessipation, and voltage supply must be taken into account when designing a low power and voltage comparator. These factors are represented in this paper. This essay compares several comparators, including complex circuit, length of design, CMOS technology, and others. A 45nm-based comparator's design, followed by a Cadence Virtuoso simulation.

Keywords: Analog-to-Digital-Converter (ADC), Digital-to-Analog-Converter (DAC), Successive Approximation Register (SAR), Low Power, High speed clock frequency, Conventional Dynamic.

Abstract: This project delivers an actual solution for managing bus pass information using a database. The app has three login for user, admin and conductor. This system offers web application as well as android application for people to get their Bus passes online. This system is helpful for users to get their bus pass online instead of standing in long line to obtain their bus passes. This system is helpful to reduce the paper work; time utilization and user get the bus pass in simple and faster way. User can again fill their account and extend the validity of card when the pass is going to expire. This system provides functionality like accessing basic information of user for and provide verification bus pass for the user without placing them in long queues. This system provides security option for user. The conductor in bus would be able to authenticate the pass by scanning the QR code provided by the passenger with a suggested device. The notification generated by the system would be send to the user in form of message such as when where and what time the card was use. This system also provides online payment facility. Index Terms: Android Mobile, QR Code, Privacy, Authentication, Online Payment, Client and Server.

Abstract: Hacking is an identifying and exploiting weakness in computer systems or computer networks. Hacking is a process of gaining unauthorized access into a computer system in order to steal, change or destroy information.

Keywords: Impersonation, Phishing scams, hacker, cracker, Netsparker.

Abstract: This research paper presents a study on the the application of machine learning methods for predicting flight delays. The objective of this research is investigating the ability of different machine learning approaches to forecast flight delays and to identify the most significant factors affecting flight delays. The study is conducted using a comprehensive dataset that includes information on airline schedules, airport congestion, weather conditions, and other relevant factors. The paper begins with a literature review of existing studies on predicting flight delays using machine learning techniques. The performance of Several machine learning techniques, such as decision trees, random forests, support vector machines, and neural networks are assessed and contrasted based on metrics such as accuracy, precision, recall, and F1 score. The outcome of the study exemplifies that machine learning algorithms are highly effective in predicting flight delays, with decision trees and random forests performing the best. The study also identifies weather conditions, airline-specific factors, and airport congestion as the most significant factors affecting flight delays. The inferences from this research paper have significant ramifications for the aviation sector, as precise projection of flight delays can assist airlines and airports better manage their operations and improve passenger satisfaction. Overall, this research demonstrates the capacity of machine learning techniques to improve the accuracy and efficacy of flight delay predictions, which can ultimately lead to a more reliable and efficient aviation system.

Keywords: Flight delays, Machine learning, Data analysis, Feature engineering, Classification algorithms, Regression algorithms, Decision trees, Feature importance, Performance evaluation, Precision, Recall, F1-score.

Abstract: Web OS for document management is a software designed for managing documents, providing a secure vault to store critical business documents. Companies now prefer storing important files in Document Management systems instead of file servers. Web OS for document management functions like a regular file system, but with enhanced capabilities. Instead of storing files on a local hard disk, files are stored within the system, facilitating easy access for individuals who need them. It operates like a network file server but with more sophisticated features.

Keywords: document management, Web, OS, file server, important files.

Abstract: Access to various systems, services, and apps requires end users to share and protect their data, which is becoming an increasingly important component of daily life. In actual email services, data disclosure occurs regularly. Secure data transfer media have long been concerned with copyright protection and authentication of multimedia materials. Due to the growing usage of the Internet and other digital technologies, the issue has become increasingly urgent. It is more complicated and challenging to implement copyright protection, nevertheless. A remedy for the copyright protection issue was proposed: digital watermarking. Both watermarking and encryption are used in the suggested method that makes use of Geofences technology to facilitate effective material sharing. Watermarking is a technique for concealing data, such as secret information, in digital material like photographs. Data security is achieved using encryption techniques. In order to prevent unwanted access, information is encoded using encryption, making it impossible for those who are not allowed to view it. With the aid of the inbuilt data verification process, the decryption key can finally be extracted by an authorised user. When user information does not correspond with embedded information, unauthorised or unlawful access can be detected. This suggested application aids in identifying unauthorised access and preventing the re-distribution of content in an email context. Also, you may create a mechanism for acknowledging mail delivery, as well as group data sharing based on a rules-based approach employing machine learning.

Keywords: Data, Machine learning, Geofencing, Security.

Abstract: Drone Redzone is an innovative application designed to facilitate the delivery of packages and goods via drones while ensuring the privacy and security of private properties. The app allows users to flag the locations of their private properties by setting and locating the radius of the property, thus enabling drone deliveries to be made by avoiding these private locations. This helps to ensure the confidentiality of private properties, government, and security-based properties. The app acts as a bridge between the user, company, and government, enabling the easy flow of new age deliveries. Drone Redzone connects users with companies that offer drone delivery services, making the process of ordering and receiving goods via drones simple and seamless. It also connects companies with government agencies to ensure compliance with all relevant laws and regulations. Drone Redzone has been developed with the latest drone technology, logistics, and safety measures in mind. Safety is a top priority, and we have implemented measures to ensure that all drone deliveries are safe and secure. We believe that our app has the potential to transform the way we think about and use drone technology. By enabling the delivery of goods via drones while maintaining the privacy and security of private properties, Drone Redzone has the potential to improve the delivery of goods via drones and reduce the overall carbon footprint of the transportation industry. Overall, Drone Redzone represents an exciting new development in the field of drone-based delivery services. We are excited to see the impact it will have on the industry and look forward to expanding its reach to new users and companies in the future.

Keywords: drone redzone, development , law , technology

Abstract: It has become easy to find accommodation close to the place of work. Previously, it wasn't easy to travel to a place of work over long distances and therefore had to lose good opportunities because we do not know where to stay and where we do not know a particular city. Users can find several paid accommodations near the workplace or desired location in this online paid guest system. Even the user can add their desired locations and get the tenant easily by uploading a photo and details of the respective location. The user can register for a login ID and password in this system. With the login ID and password, the user can log in. After logging in, the user can publish the paid guest post by adding details and photos of the location. He can also see interested users in his downloaded message. The uploaded post can be removed or deleted. The user can also see the paid accommodation, and after getting the desired place, he can select the place he is interested in. After choosing the desired location, the user will get the owner's details, he can get in touch with the owner and make an appointment for further processing.

Keywords: Accomodation, Travelling Users, Login ID and Password

Abstract: The benefits of implementing a web operation platform for businesses, specifically focusing on the Diurnal Pay Envelope Employment operation, which aims to provide a platform for daily wage workers to earn according to their skills and help them upskill through training centers. Such a platform can streamline the hiring process for businesses and reduce the burden of manually hiring workers, which is often time-consuming and expensive.By providing a platform for daily wage workers, businesses can easily find workers with the required skillset, reducing the time and effort required for hiring. Additionally, such a platform can help provide opportunities for weaker sections of society to earn a livelihood, which can have a positive impact on the overall economy.Furthermore, the training centers can help these workers upskill and acquire new skills, which can lead to better job opportunities and higher pay. This, in turn, can help in reducing poverty and inequality, which is a crucial need for many developing countries.Overall, implementing a web operation platform like the Diurnal Pay Envelope Employment operation can have many benefits for businesses, workers, and the economy as a whole. Index Terms –Diurnal, Employment, Workers, Pay.

Abstract: The "Advisory System for Personal Expenses" is a smart device application that aims to address poor budgeting performance by utilizing user income, savings, and budget amounts as inputs and providing expense analysis and advice to help users achieve their saving goals. The system incorporates Business Intelligence (BI) technology, offering historical, current, and predictive views of data to support user decision-making. The objective of this paper is to provide a comprehensive overview of the "Advisory System for Personal Expenses" project, including the background, literature review, methodology, objectives, results, and conclusion. Index Terms: Personal expenses , advisory system , advisory , expenses

Abstract: The abstract for a project on creating a smart home using Google Assistant and Alexa with the NodeMCU ESP8266 could look something like this: In this project, we aim to create a smart home system using the NodeMCU ESP8266 microcontroller and integrate it with both Google Assistant and Alexa voice assistants. The system will allow users to control various aspects of their home, including lighting, temperature, and security, using voice commands through either Google Assistant or Alexa. The NodeMCU ESP8266 will serve as the central hub of the smart home system, connecting to various sensors and actuators throughout the home. We will program the NodeMCU to receive commands from Google Assistant and Alexa and translate them into actions on the connected devices. To achieve this, we will use the MQTT protocol to establish communication between the NodeMCU and the voice assistants. We will also make use of various APIs provided by Google and Amazon to enable voice control functionality. The smart home system will be scalable, allowing users to add new devices and functionalities easily. We will also ensure that the system is secure, using encryption and authentication protocols to protect user data and prevent unauthorized access. Overall, this project aims to demonstrate the potential of the NodeMCU ESP8266 microcontroller in creating a powerful and versatile smart home system that can be controlled using voice commands through both Google Assistant and Alexa

Abstract: An application that works with the assortment and dispersion of surplus food from food enterprises and PGs could assist with expanding the productivity and viability of food gift endeavors in India. Food recipients may be able to request food donations based on their specific requirements, and food donors may be able to easily schedule pickups for surplus food through the use of such an application. By enabling more precise tracking and management of surplus food, technology could also contribute to a reduction in food waste. In recent years, India's economic growth and development have advanced significantly. However, the nation faces a significant obstacle in the form of hunger, malnutrition, and food insecurity. This examination paper investigates the causes and outcomes of food weakness in India, including neediness, inconsistent dispersion of assets, unfortunate foundation, and environmental change. In addition, it discusses the effects of hunger and undernutrition on individuals as well as society, including malnutrition, health issues, poverty, and social unrest. The paper suggests addressing poverty, improving distribution channels, increasing food production, and adapting to climate change as potential solutions. It emphasizes the significance of government programs and policies, such as the National Food Security Act and the Integrated Child Development Services, in reducing food insecurity and improving nutritional outcomes. This research emphasizes the critical need for India to overcome food insecurity and ensure that all of its residents have access to sufficient, nutrient-dense, and reasonably priced food. By taking proactive steps to address this problem, India can create a society that is more just and long-lasting as well as improve the health and well-being of its people.

Keywords: Hunger, Undernutrition, Food insecurity, Food waste, Food donation, Food delivery application, Public distribution system (PDS), Malnutrition, Food Access, Food supply chain, Social responsibility, Humanitarian aid. Hunger, Undernutrition, Food insecurity, Food waste, Food donation, Food delivery application, Public distribution system (PDS), Malnutrition, Food Access, Food supply chain, Social responsibility, Humanitarian aid.

Abstract: The proposed web application is designed to provide a platform for patients and doctors to interact efficiently and effectively. The patient panel includes several features that enable patients to manage their medical data, book hospital appointments related to their health issues, read blogs on their diseases, purchase online medicines through the pharmacy, and use QR codes to access their medical information. The doctor panel, on the other hand, enables doctors to manage their appointments with patients, retrieve patient data through QR code scanning, and check the contents of medicines prescribed to patients. The application is built on modern web development frameworks such as ReactJS, NodeJS, and MongoDB, which provide a secure and scalable environment for data management. The proposed methodology includes a development process that incorporates rigorous testing and quality control to ensure that the application meets the highest standards of usability and security. The technology stack includes modern web development frameworks that offer the flexibility and scalability necessary to accommodate future expansion and growth. The potential results and outputs of the proposed web application are significant. By enabling patients to manage their medical data and access healthcare services online, the application can enhance patient engagement and satisfaction. Doctors can also benefit from the application by managing their appointments and accessing patient data quickly and efficiently. The web application has the potential to reduce healthcare costs by enabling patients to access healthcare services remotely, reducing the need for physical consultations. The application can also improve patient outcomes by providing patients with easy access to healthcare services, enabling them to manage their health more effectively.

Keywords: QR code, Health Card, Encryption, Cryptography, Decryption.

Abstract: Humans with body health problems seek medical treatment immediately but when they have mind-related problems they are reluctant to seek medical treatment because brain has no pain sensors. When Prefrontal Cortex (PFC) of a human is under stress and it is partially/fully shutdown, Amygdala dominates stopping humans from seeking medical care. Consequently, according to scientific mind model, a Complete Mind (CM) is not available. CM is an algorithm based on EEG data from neuron firing in Microbiome-Gut-Brain-Axis (MGBA). Surprisingly, lack of CM leads to psychological & neurological problems resulting in chronic inflammation that is a leading cause of cancer and heart disease. This paper demonstrates the use of a stress-controlled LEGO robot to detect psychological & neurological problems. The EEG sensors and control electronics present in a Fabric- and/or Tattoo-embedded (or skin-patch-embedded) Micro System (FTIMS) to control the LEGO robot by a mind state (stress, anxiety, empathy, etc.). Earlier demonstrated mind’s attention level control of the LEGO robot can be extended for empathy, anxiety, depression, etc., which needs EEG signals from brain parts responsible for these factors. This shows that emotional control of a robot is possible, and thereby open the door to exploring how people can indicate their need for mental health services by their ability or inability to mentally control a LEGO robot. The research conducted in three phases, (a) multi-sensor EEG for approximate signals coming from different brain parts, (b) accurate identification of brain parts involved certain neurological phenomena using fMRI/EEG system, and (c) study role of EEG signals coming from MGBA identifying role of Microbiome communication with Amygdala, is unique in the world. Ketogenic diet and blackseed oil (Nigella Sativa) are emerging as an effective treatment for most cancers.

Abstract: The project's goal is to create a number of network utilities needed to efficiently monitor user activity over a LAN network. It seeks to create an integrated software solution that enables a network administrator to view his users' everyday activities from a distance through LAN. This tool enables you to build statistics reports with crucial data and receive comprehensive information on the activities your employees are involved in during working hours. Software captures photographs at pre-determined intervals covertly for the user to allow for a more thorough monitoring of the activities taking place on user PCs. These snapshots are then chronologically saved into a database. These snapshots provide comprehensive information about all users' activity in a rapid gallery view.

Keywords: Network Monitoring, client Activity Tracking, Snapshot Capturing, Client Data Storing, Network Visibility

Abstract: Several security methods have been suggested and implemented for some essential activities in public or commercial institutions where security has become an increasingly important problem. Over the past two decades, face recognition has attracted a lot of interest. It may be attempting to investigate the broad range of commercial and security applications as one explanation for this. Automation is the development and use of technology to manufacture and provide goods and services with little or no human involvement. An automated luggage counter that combines software and hardware technology can be created by using automation and facial recognition principles. The user can store their valuables in the counter and only utilize facial detection and identification to open the system.

Keywords: LBPH, OpenCV, Haar Cascade.

Abstract: The COVID-19 pandemic has created an urgent need for efficient and accurate diagnostic methods. X-ray imaging has been widely used in detecting COVID-19, however, the interpretation of X-ray images requires expertise and is prone to errors. In order to improve the accuracy of COVID-19 diagnosis using X-ray images, a detection system can be developed using a combination of Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). The proposed system will aim to automatically detect COVID-19 from X-ray images with a high level of accuracy. The proposed system will use a pre-trained CNN model to extract features from the input X-ray images. The extracted features will then be fed into an RNN to capture the temporal information in the image sequences. The RNN will be trained to classify the X-ray images into two categories: COVID-19 positive and negative. The system will be trained using a large dataset of X-ray images from COVID-19 positive and negative patients. The dataset will be divided into training, validation, and testing sets. The system will be optimized using a loss function and backpropagation algorithm. The performance of the system will be evaluated using various metrics such as accuracy, sensitivity, and specificity. The system will also be compared with other state-of-the-art methods for COVID-19 detection from X-ray images. Overall, the proposed system has the potential to provide an efficient and accurate method for COVID-19 detection using X-ray images. The outbreak of COVID-19 has created an urgent need for effective and efficient diagnostic methods. This project proposes a COVID-19 detection system that utilizes a combination of Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to automatically identify COVID-19 from X-ray images with high accuracy. The system extracts features from the input X-ray images using a pre-trained CNN model, and then employs an RNN to capture the temporal information. The RNN is trained to classify X-ray images into COVID-19 positive and negative categories using a large dataset of COVID-19 positive and negative patients. The system is optimized using a loss function and backpropagation algorithm, and its performance is evaluated using various metrics such as accuracy, sensitivity, and specificity. The proposed system has the potential to provide an efficient and accurate method for COVID-19 detection using X-ray images.

Keywords: Convolutional Neural Network, Recurrent Neural Network, chest X-rays, LSTM,

Abstract: Figure 'n Fit is a weight management organization that offers both weight loss and weight gain treatments. Currently, the organization maintains all patient records manually on paper. However, they are in the process of developing an application that will digitize and simplify their system. This will make it easier for patients to access their information and for the organization to manage their records efficiently. The Figure 'n Fit application provides various facilities to users, including personal dietitians, fitness centers, and nutrition consultants. These services are accessible globally through the internet, which eliminates the need for physically visiting and hiring different dietitians. Users can set daily reminders and maintain daily reporting from home, which makes it easier for them to live a healthier and fitter life. The Figure 'n Fit application is designed to make weight management more accessible to everyone, regardless of their location or lifestyle. The application is easy to use and provides users with personalized recommendations based on their individual needs and goals. This helps users to achieve their weight management goals in a way that is safe and sustainable. The organization has established a firm foothold in its industry and has a reputation for providing high-quality services to its clients. The organization's belief that customer satisfaction is as important as their products and services has helped them to build a vast base of loyal customers. The organization employs 4 individuals who are dedicated to their respective roles and work hard to achieve the common vision and larger goals of the company. The Figure 'n Fit organization aims to expand its line of products and services to cater to a larger client base in the future. This will enable them to provide weight management services to even more people and help them to achieve their weight management goals. The organization is located in Surat and is easily accessible through various modes of transport, which makes it convenient for people to avail of their services Index-Terms: Traditional, Modern, Culture, Practice.

Abstract: The fuel delivery concept is a modern and innovative approach to the traditional way of purchasing fuel. Rather than going to a gas station, customers can use an on-demand fuel delivery service to have fuel delivered directly to their location. This concept offers numerous benefits, including convenience, time-saving, and reduced carbon emissions. The fuel delivery concept is made possible through the use of advanced technologies, such as GPS tracking, mobile payments, and cloud-based software. While there may be challenges and regulations that need to be addressed, the fuel delivery concept has the potential to transform the fuel industry and offer a better experience for both consumers and fuel providers.

Keywords: fuel delivery, gas station, sustainable energy.

Abstract: Electronic health records (EHRs) may be replacing paper records at your healthcare provider's facility or they may already be in use. Specialist organisations can use data from EHR to work on the quality and productivity of your consideration all the more effectively, but EHR doesn't alter the security or security assurances that apply to your well-being data. At all stages of the public cloud plan, this duty intends to provide a secure cloud framework for the handling of events and utilisation of solid figuring administrations. This eliminates risks to internal and external security. As a result, information protection, data reliability, verification, and approval are achieved, and active and covert attacks from the cloud network cloud are eliminated. Encourage the development of a reliable cloud system to ensure capacity management and registration at all levels of the public cloud consumption model. ADSS is an effective mechanism for sharing medical data in a public cloud environment while maintaining patient privacy and data security.With the vivacious improvement and utilization of cloud Staffs figuring, a constantly creating number of clients are moving their Staffs information to cloud servers. The methodology of gushed selecting Staffs quiets the eats up of information the board, information sorting out, Staffs and capital usage on contraption, programming, and work constrain Staffs structures for upkeeps, and so on. Neglecting the manner by which the upsides of cloud Staffs setting up, a couple of obstacles effect and make the undertakings Staffs hesitant to move the information to the cloud server. Open cloud Staffs is affirmed and obliged by open cloud servers (PCS), which Staffs can't be trusted. PCS may take or get the information data staff set away by the clients. Thus, a wide level of security is contemplated. Staffs are proposed to guarantee security in the cloud, for example, remote information Staff uprightness, remote information sharing, and so on.

Keywords: Attribute-based encryption, cloud computing, data sharing, searchable encryption.

Abstract: The usage of mobile applications for charitable donations via connecting to several reputable NGOs is discussed in this study. The idea behind having a mobile app for giving to different NGOs is to make a person utilise the app effectively and to allow them to efficiently and successfully give money or commodities. A separate NGO website or the provision of their Account number or as such has replaced individual donations. As a result, these mobile applications turn a lot of laborious effort into intelligent work. An individual can fulfil any needs and provide money, food, clothing, and other items via the app. By using API software, one may locate NGOs in their area without having to search through numerous individual websites or contact details. In those days, individuals. Mobile donation apps have become increasingly popular in recent years due to their convenience and accessibility. These apps allow users to donate to a variety of social welfare causes, such as poverty alleviation, disaster relief, education, healthcare, and environmental conservation, among others. One of the advantages of using mobile donation apps is that they provide a simple and user-friendly interface for making donations. Users can easily navigate through the app to find a cause that resonates with them and donate using a variety of payment options, such as credit cards, PayPal, or mobile wallets.

Keywords: Mobile Application, NGOs, Online Donation, Welfare.

Abstract: In the contemporary digital era, the malware presents a substantial challenge to internet users, particularly with the rise of polymorphic malware that persistently alters its discernible features to evade detection by traditional signature-based models. This advanced malware variety, which boasts a dynamic design and inherits traits from multiple malware types, differs significantly from its conventional counterparts. The proposed research aims to examine and analyse the behaviour of malware executables, mainly focusing on their polymorphic attributes, to enhance cybersecurity through better understanding and detection. Tackling the growing complexity and volume of malicious software is arduous, prompting researchers to employ machine learning techniques to decipher the underlying patterns and models within this intricate landscape, thereby keeping pace with malware's continuous evolution. This comprehensive review sheds light on using machine learning in the context of malware analysis for Windows environments, explicitly targeting Portable Executables. In our analysis of the existing literature, we classify the studies based on their objectives, the malware-specific data and features, and the machine-learning approaches they apply. Furthermore, we delve into the challenges and issues tied to dataset usage and identify the dominant trends and promising future directions.

Keywords: Machine Learning, Cyber Security, Malware, Malware Analysis

Abstract: To manage and analyze student ranks and outcomes, a web-based project called Student Performance Analysis was developed. It also features extra modules to figure out the students' SGPA and CGPA. Reduce manual errors and transform the output system into a computerized system are its two main goals. A time and effort-saving performance report generator is part of the project and generates reports by year, branch, section, and subject. Students can view their academic success as the technology aids teachers in analyzing findings and generating reports with a single click. It centralizes data administration and is a user-friendly web application that is available from anywhere. The approach benefits students, teachers, and college management since it raises production while enhancing educational quality and student achievement.

Keywords: JavaScript, SQL (Structured Query Language), PHP (Hypertext Preprocessor), XAMPP (Cross-Platform, Apache MYSQL, PHP and Perl).

Keywords: measures, indicates, responds, active and passive sensors, third party applications, analog and digital sensors, posture or movement, heel, toe mounds, inner arch, outer arch and android application interface.

Abstract: A virtual assistant is a software agent that can perform tasks or services for an individual. Sometimes the term "chatbot" is used to refer to virtual assistants generally or specifically those accessed by online chat. Virtual Assistant (VA) is a term that applies to computer-simulated environments that can simulate physical presence in places in the real world, as well as in imaginary worlds. This report discusses ways in which new technology could be harnessed to create an intelligent Virtual Personal Assistant (VPA) with a focus on user-based information. This project is a technical brief on Virtual Assistant technology and its opportunities and challenges in different areas. The project focuses on virtual assistant types and structural elements of a virtual assistant system. In this project, we tried to study virtual Environment and virtual Assistant Interfaces, and the paper presents applications of virtual assistant that helps in providing opportunities for humanity in various domains. This project also describes the challenges of applying virtual Assistant technology. In today's advanced hi-tech world, the need of independent living is recognized in case of visually impaired people who are facing main problem of social restrictiveness. They suffer in strange surroundings without any manual aid. Visual information is the basis for most tasks, so visually impaired people are at disadvantage because necessary information about the surrounding environment is not available. With the recent advances in inclusive technology, it is possible to extend the support given to people with visual impairment.

Abstract:  An emergency is an unexpected happening that needed immediate intervention due to its degree of threat. A vehicle breakdown is a specific emergency that has caused vehicle owners and travelers frustrated moments, especially when it happened in an unfamiliar location. Furthermore, access to competent vehicle technicians and other related services is limited and can be worsened by language barriers and unfamiliar areas. In such situations locating nearby electric vehicle spare parts/service shop becomes important. The application solves this problem by providing users to ability to search for nearby service/spare part shop so that they can get the desired help from them. Thus it eliminates the risk of disaster and provides timely help to the user. The system has a user module where in the user can search for nearby shops providing desired service. He can raise a request to get desired service from the team. The second module consists of an admin app which can be used by garages and shops to serve the request. With the help of admin app they can add, edit and update their services and products. Thus our proposed system tries to bridge the gap between user and shops..

Keywords:  Electric Vehicle, Locator, Nearby, Emergency

Abstract: Blockchain is a secure, distributed, peer-to-peer, and open ledger. Blockchain is a chain of blocks that contains transaction information. It is meta-technology as it affects other technology. Blockchain is a digital decentralized digital ledger made up of blocks that record data across a peer to peer networks. It is used for the secure transfer of items like money, property, contracts, etc.

Keywords: Peer-to-peer, decentralized, distributed.

Abstract: The Public delivery machine is a first-rate supply of earnings in growing nations like India. Earlier to order a price price tag humans  needed to  waste a whole lot of time with the  aid of using status in an extended queue Bus wishes a  conductor to accumulate cash and problem price price tag to every  passenger; it's time consuming, guide blunders like flawed distribution of ticket, passenger visiting without ticket,  foreign exchange and plenty of different troubles occur. To triumph over this problem’s, we're going to recommend a gadget referred to as Smart cashless ticketing gadget for bus (without conductor without stop).. This machine elaborates the set up of Smart Card reader circuit in every and each bus to calculate the price price tag charges Depending upon the distance (quantity of stations) travelled; the corresponding price is mechanically deducted  From the user’s money owed and via GSM module message is ship on passengers mobile. This makes the cashless ticketing system.

Abstract: The remote control trash collector for lake water is a device designed to collect floating debris and waste from water bodies, particularly lakes, in a convenient and efficient manner. The system comprises a remotely controlled vehicle equipped with a debris collection mechanism, such as a conveyor belt or suction pump, and a waste storage compartment. The device aims to minimize the environmental impact of waste and debris in water bodies and provide a cost-effective solution for cleaning lakes, reservoirs, and other water resources. It is also designed to reduce the manual labor required for cleaning up lakes, making the process safer and more efficient.

Keywords: Trash Collector , DC Motor , Conveyor Belt ,  Chain & Sacket.

Abstract: Procurement in Afghanistan has been overseen by a number of commissions and independent bodies, as well as the National Procurement Authority, that served as an office of the President. The award and implementation of projects has been a challenge throughout the procurement process, however, there have been specific factors and challenges that affected the successful implementation of IT and ICT projects in Afghanistan. These factors have caused the complete shutdown of the projects, delay in the timeline and signing off, compromise to the quality of equipment and compromise to the quality of implementation in the projects. In any case, the factors have proved to affect successful implementation of IT and ICT Projects in Afghanistan. In this study, the administrative, political and technical factors that have affected successful implementation of IT and ICT projects in Afghanistan, with possible recommendations and scope for future researchers. Key Words: Information Technology Projects, Information and Communication Technology in Afghanistan, IT and ICT, Factors affecting successful implementation of IT Projects, Procurement of IT and ICT projects in Afghanistan, Success of IT and ICT Projects

Abstract: Today speech technologies are commonly available for a limited but interesting range of tasks. The technologies enable machines to respond correctly and reliably to human voices and provide useful and valuable services. As communicating with a computer is faster using voice rather than using a keyboard, people will prefer such a system. Communication among human beings is dominated by spoken language, therefore it is natural for people to expect voice interfaces with computers. can be accomplished by developing a voice recognition system - speech-to-text which allows the computer to translate voice requests and dictation into text. Voice recognition system - speech-to-text is the process of converting an acoustic signal which is captured using a microphone to a set of words. The recorded data can be used for document preparation. In the project is to able automated notes maker from audio recordings application based on AI, ML to make the computer understand speech commands and convert it into text and then PDF/WORD format.

Keywords: Automatic speech recognition, Technology, Automated captions, Qualitative data, Transcription.

Abstract: Wind energy is one of the renewable energy sources that are being used more and more often these days to supply the excessive demand for energy. It is necessary to have a good wind turbine tracking system for environmentally friendly energy production. As most windmills are located in remote areas, it takes a lot of time and energy to continuously monitor them. In contrast to conventional methods, using digital equipment that includes sensors and controls will provide accurate results. In the research "IoT based Windmill parameter monitoring system", sensors that might be built on a windmill are used to measure factors including temperature, humidity, vibrations, air pace, and some other characteristics. The output from these sensors enables us to get the information necessary for tracking the characteristics of the windmills. By using this information, we can prioritize and automate security measures. Also, for remote tracking, the data from sensors is shown all at once on a dashboard. The admin and the responsible authorities may see this dashboard, and if necessary, it may be recorded for later use. Important statistics like energy, power, and cash gained may also be created with its help. Professionals may use the same information for any layout modifications, largely based on the materials and geometric parameter requirements.

Keywords: IoT, Windmill, Monitoring system, Sensors, Management

Abstract: The magnetic wing turbine is a promising technology for energy harvesting applications, which utilizes a magnetic field to rotate the blades of the turbine. This technology provides revolutionized way for generating energy and sustainable solution for generation of power. The magnetic wing turbine generates electricity by utilizing the movement of air to rotate a rotor equipped with permanent magnets. The rotation of the rotor creates a magnetic field that induces a current in a nearby coil, which is then converted into usable electricity. The design of the magnetic wing turbine offers several advantages over traditional wind and hydro power systems, including higher efficiency, reduced noise pollution, and improved durability. In this paper a review about Energy Harvesting Using Magnetic Wind Turbine is presented.

Keywords: magnetic wing turbine, energy harvesting, permanent magnet, magnetic field.

Abstract: Silkworm rearing is a part of the agro-based sector known as sericulture. The method of raising silkworms now in use has to be improved. With the aid of electrical and electronic components, every step in this project has been developed to give the farm with total protection. By implementing automation in feed supplementation, temperature management, and moisture control, it helps farmers. Several temperature ranges and levels of moisture are needed for silkworm growth. The arduino microcontroller, temperature, and moisture sensors are used to establish this. This project will provide farmers with financial assistance so they won't have to spend as much time on the sericulture farm

Keywords: Silkworm, Silk, Automation.

Abstract: Nowadays Customer segmentation became very popular method for dividing company’s customers for retaining customers and making profit out of them, in the following study customers of different of organizations are classified on the basis of their behavioural characteristics such as spending and income, by taking behavioural aspects into consideration makes these methods an efficient one as compares to others. For this classification a machine algorithm named as k- means clustering algorithm is used and based on the behavioural characteristic’s customers are classified. Formed clusters help the company to target individual customer and advertise the content to them through marketing campaign and social media sites which they are really interested in. Keywords. Data visualization, Data analysis, Machine learning, Customer segmentation, K-means algorithm

Abstract: An adder is used to physically realise addition, which is a fundamental operation in microprocessing and digital signal processing technology. Two common high-speed, low-power adder architectures are the carry-lookahead adder (CLA) and the carry-select adder (CSLA). Using a hybrid CLA architecture, which substitutes a small-size ripple-carry adder (RCA) for a sub-CLA at the least significant bit positions, can increase the speed performance of a CLA architecture. On the other hand, by using binary-to-excess-1 code (BEC) converters, the power dissipation of a CSLA using full adders and 2:1 multiplexers can be decreased. Many CLAs and CSLAs have separate designs that have been discussed in the literature. A direct comparison of their results based on the design metrics would be helpful. To enable a comparison, we constructed 32-bit accurate and approximate additions in homogeneous and hybrid CLAs, as well as CSLAs with and without the BEC converters. We looked at a 32/28 nm complementary metal-oxide semiconductor (CMOS) process with a typical-case process-voltage-temperature (PVT) specification for the gate-level implementations. The findings indicate that, in terms of speed and power, the hybrid CLA/RCA architecture is preferable to the CLA and CSLA structures for performing precise and approximative additions.

Keywords: arithmetic circuits; ripple-carry adder; carry-lookahead adder; carry-select adder; digital design; standard cells; CMOS

Abstract: Food image recognition for inventory tally is a technology that allows for the automated identification and quantification of food items in a given inventory using image recognition algorithms. By analyzing images of food items and comparing them to a database of known food items, the system is able to accurately identify and count the number of each type of food present in the inventory. This technology has the potential to greatly improve the efficiency and accuracy of inventory management in food-related industries, such as restaurants, supermarkets, and food distribution centers. It can also potentially be used to help with food waste reduction efforts by allowing for more accurate tracking of expiration dates and helping to ensure that all food items are used before they go bad.

Keywords: CNN, Object Detection, Food Detection, Inventory Tally, Deep Learning.

Abstract: In the modern competitive era, the viability of a business depends on its flexibility and its ability to adapt to any circumstance. One way of achieving this is through modeling and management of the business processes in use. Business Process Management (BPM) is a systematic approach for making organization’s processes more efficient and dynamic in order to meet the changing needs of businesses. This paper provides a review on BPM and modeling. Through the study of industrial robots and particularly, the industrial robotic arms, we better understand how business processes are modeled and how this method facilitates the identification and optimization of the current processes. The modeling of the processes was carried out using the Business Process Management and Notation 2.0 (BPMN 2.0) methodology. More specifically, the overall operation of a robotic arm was captured, while complex sub-process and the servo motor operation, which is the driving force of the industrial applications, were analyzed in depth. The Bizagi Modeler tool was used to visualize the processes of the industrial robotic arms.

Keywords: BPM, Business Process Modeling, BPMN 2.0, Robotic Process Automation, Industrial Robotic Arms

Abstract: In this research paper, a study on Light Fidelity (LI-FI) technology has been done for data transmission. LASER is used for data transmission in proposed technique using LI-FI. A large number of data packets is transferred through light communication technology within less time period compared to existing techniques. Optical channel is used to transfer data between sender and receiver using specific data transmission protocol. In LI-FI we have used an optical channel to encode an information into an optical signal. A receiver is there at the end to reproduces the message received from the optical signal. Here we are sending audio and data over Laser light to solar panel. For Audio signal transmission, the positive end of Laser is connected to 5v supply, ground of Laser is connected to aux cable to audio device, the signal amplitude fluctuation is transmitted to solar panel, the solar panel output is connected to amplifier circuit connected to speaker. For Data transmission Laser source is connected to Arduino uno microcontroller, the text data is converted to digital output in 1, 0 forms to the solar panel. At the receiving side the solar panel is connected to Arduino uno, in Arduino a threshold value of signal is defined, if value above threshold defined value is 1, if value below threshold defined value is 0. The data that is received is then decoded to text form is taken out via serial monitor or lcd display.

Keywords: Wireless communication, Visible light communication, Audio transmission, Data transmission.

Abstract: The sample and hold procedure is carried out using a sample-and-hold circuit, also known as a track-and-hold circuit. It is difficult to design these circuits since they must work at the greatest signal levels and speeds. To obtain the best performance, the trade-off between noise and distortion needs to be carefully balanced. ADC is essential for many applications, including wireless communication and digital signal processing, because virtually every real-world analogue signal can be converted into a digital signal using an ADC.

Keywords: Sample and hold, track and hold, Analog-to-Digital Converter (ADC).

Abstract: R2D2 is an AI- driven assistance robots to enhance passenger experience. These autonomous robots have conversational skills, mapping abilities, and exceptional sensors. R2D2 uses AI that enables recognizing questions and providing answers. The robots have been deployed at railways to assist customers with directions and other train information. From a software perspective, when there is an obstacle in front of it, the robot must find the best way to move over. We had some trouble making the robot understand that the trolley collectors that push the trolleys back to their place are a moving obstacle. We had to tweak the software umpteen times, shows videos and captures photographs of the floor, as well as helps connect the customer/passenger to any help desk through its image recognition features. Added with great ground sensors, R2D2 can detect obstacles that are stationary or dynamic. If a passenger suddenly comes in front of the robot, it will stop. It is equipped with SLAM (Simultaneous Localization and Mapping) technology that helps it map the entire railway station.

Keywords: Mapping ability, SLAM (Simultaneous Localization and Mapping), conversational skills, software umpteen

Abstract: Fruit ripening is a normal process. Fruit naturally produces ethylene, which is what causes fruit to mature. But to speed up this process so their product will hit the market earlier and they can optimise profit, dealers and sellers frequently use chemicals like CaC2. Chemicals are used to preserve fruits in storage. This substance reacts with moisture to create ethylene, which causes the berry to ripen. Contrary to when a fruit ripens naturally, which results in uneven ripening because natural ethylene present in fruits is unevenly distributed, when ethylene is present in large quantities and comes into contact with the fruit's surface area, it uniformly causes the fruit to ripen.Therefore, the suggested method obtains a picture of the fruit being tested and compares it to the characteristics of naturally and artificially ripened fruit before providing an output with a probability. This technique uses a smartphone running an Android programme.

Abstract: In this project, a reverse vending machine (RVM)-inspired automatic recycle bin with a reward element is proposed. The device is essentially built in a regular recycle bin that is fitted with a microcontroller and a variety of sensors. The sensors in charge of identifying user information are used throughout. The code will appear on the LCD once the process is finished. The user must scan the QR code that is printed on the device in order to redeem their points.

Keywords: component, formatting, style, styling, insert

Abstract: Cardiac arrhythmia is a hazardous disease that is characterized by an irregular heartbeat. Dysfunctional nodes in cardiac muscles lead to irregular rhythm of heartbeat patterns which induce severe health problems such as cardiac arrest. This irregular heartbeat could be either too slow (less than 60 beats /min) or fast (greater than 100 beats /min). This disease can happen to people at any age. Since it is a life-threatening disease, early arrhythmia diagnosis is useful to save lives. An Internet of Things platform is useful to modernize the health care sectors and this helps to save lives. An IOT platform for the prediction of arrhythmia disease using a device that continuously acquires the patient's ECG signal and processes the ECG signal. Using this device people can check their heart condition by the ECG signal in their home. While processing if there is an emergency it gives an alert to the physician. This helps the physician to analyze the disease as early as possible.

Keywords: ECG telemetry system, ECG sensor, Electrodes, Heart rate, Temperature.

Abstract: Maniacal case accordingly creating what is going on of hanging is staggeringly unprecedented. To perceive reckless/lethal hangings, the appraisal of wrong doing area on various focal issues in undisturbed condition followed through posthumous review is vital to track down the certified truth. The most utilized technique for self-destruction is by draping oneself to a fan. Selfdestruction by hanging is extremely disturbing around the world.  India has the most noteworthy selfdestruction rate in the South-East Asian locale, as per the World Health Organization's most recent report. The report delivered a day prior to World Suicide Prevention Day in 2019, fixed India's self-destruction rate at 16.5 suicides per 100,000 individuals. Since the beginning of the pandemic because of the Covid, the self-destruction rates are increasing in decent number. According to a report of National Crime Records Bureau (NCRB), Government of India, a seriously decent number of hanging cases are accounted for each year. The vast majority of the hanging cases are usually self-destructive. Numerous frameworks have been proposed to forestall these cases. Consequently, this avoidance frameworks will help in saving lives to beat this issue, the fundamental target of this paper is to lessen the self-destruction endeavors happening.

Keywords: Ceiling fan, Weight, Spray,Control.

Keywords: Quick response code (QR Code), Smart dairy farming (SDF).

Abstract: Due to the ongoing reduction in chip size, power minimization is the primary design focus in VLSI circuits. The development of VLSI systems relies heavily on CMOS technology because it uses less power. Modern integrated circuit (IC) designers aim to create digital circuits with low power consumption in very large scale integration (VLSI) ICs. This is done to increase the circuit's battery life, especially if it is intended for wearable technology. Counters are frequently employed in digital circuits, and these counters demand a lot of power. Reduced power usage across the board is necessary to have an effective digital system. Thus, this paper aims to provide the various power optimization techniques that can be incorporated in Johnson Counter design in order to reduce the power dissipation of the counter. Also these techniques can be incorporated in other counter design as well.

Keywords: Complementary Metal Oxide Semiconductor (CMOS), Integrated Circuit (IC), Very Large Scale Integration (VLSI), Low power, Johnson Counter, Flip-Flop.

Abstract: Zomato, an online food delivery platform, has been facing challenges in improving their sales performance and gaining a competitive edge in the market. In response, this Power BI project on business sales data analytics of Zomato aims to provide valuable insights into their sales trends, customer behaviour, and factors impacting their sales performance. Specifically, the project will identify the most profitable customer segments for Zomato and develop targeted marketing strategies, identify cross-selling and upselling opportunities to increase revenue, analyse Zomato's sales performance compared to their competitors and develop strategies to gain a competitive edge in the market, and develop a sales forecasting model to predict future sales performance...

Keywords: Data analysis, Power BI, Zomato, Data visualization.

Abstract: The motive of our mission is to offer a simpler and extra efficient way for the pet owners to feed their pets. The system makes use of Internet of Things and Digital Image Processing for implementation. At First, In the project a pet call is provided using a recorded voice through a speaker to indicate feed time of the pet is initiated. The Ultrasonic Sensor is placed in order to detect the pet in front of the system. Once pet detection is done the camera is switched on and Camera captures image of the pet and processes. If the pet is recognized as required pet, a dc motor will be activated to dispense food.

Keywords: Automatic Feeder, Computer Vision, Digital Image Processing, Neural networks, Pet Food Dispenser.

Abstract: Today web services are used by billions of people for various purposes like news, E-mail, and browsing information. Nowadays people have several accounts in email, social networks, and many services. All of these employ traditional authentication method such as password authentication. Having different or various kinds of passwords for different accounts and remembering or memorizing those passwords is very difficult. So, the user ends up with a simple password. But this will become easy for hackers, especially during the transaction. For these problems, this project provides a password less multifactor authentication system. This includes face authentication, voice authentication, and hardware authentication method.

Keywords: MFA, Passwordless, Attiny85, USB

Abstract: The SOSCo Android App is an innovative application for men, women, seniors, students and anyone who needs help in an emergency. It can be used to find and help people in need. With the rapid adoption of smartphones and falling internet costs, providing an easy way to help people facing emergencies and needing help from service providers such as police, media, ambulance, and fire departments in emergencies. can do. Emergency help android apps can show people's exact location so service providers can know where they are and help them.

Abstract: The problem with electric vehicle charging infrastructure is building enough charging stations in the right places and having the network support their smooth operation. However, not all EVs and plugs are created equal. In particular, EV charging connector or plug type standards vary by geographic region and modeA dynamic wireless vehicle charging system is a technology that allows electric vehicles to charge wirelessly while in motion. This system employs a series of wireless charging coils embedded in the road, which transfer energy to a receiver mounted on the vehicle's undercarriage.

Abstract: Nowadays Customer segmentation became very popular method for dividing company’s customers for retaining customers and making profit out of them, in the following study customers of different of organizations are classified on the basis of their behavioral characteristics such as spending and income, by taking behavioral aspects into consideration makes these methods an efficient one as compares to others. For this classification a machine algorithm named as k- means clustering algorithm is used and based on the behavioral characteristic’s customers are classified. Formed clusters help the company to target individual customer and advertise the content to them through marketing campaign and social media sites which they are really interested in.

Keywords: Machine learning, Customer segmentation, K-means algorithm

Abstract: Facial recognition is a technology that can match a human face from a digital image or video, against a database of stored faces. Without using additional biometrics, the targeted person can be identified and verified using only their face. Despite being a simple task, it is thought to be the most complex and difficult for computer vision. The clear detection, tracking, and recognition of a face utilising image processing will be demonstrated in this work. Face recognition is utilised in several biometric, security, and surveillance applications. In this project, Viola-Jones and PCA algorithms are implemented using MATLAB. Through serial data communication live updates is given to control room. Keyword: Viola-Jones, PCA, Serial data communication, MATLAB, Wi-Fi, Live update.

Abstract: A With increase in economic growth more and more people are able to afford vehicles to commute. Especially in metropolitan cities like Bengaluru where the number of people using two-wheelers and cars are high. The number of cars and vehicles in cities have increased by two folds which has created the non-availability of parking slots which in turn leads to traffic jams, congestions etc. Using information and Communication technology with sensors/ embedded systems and IoT the problem of parking can be addressed. Along with that the vehicles can be classified on the basis of their size for a better parking experience. We aim to address the parking availability at malls or different parking complexes in the city. The customer who wishes to find slot in a particular mall/ parking area would check list of availability of free slots using Self Interactive KIOSK machines. The machine is implemented with features to freeze parking slot, cancel the slot and view the list of free slots. Sensors are used to detect if a slot is free or blocked. Edge based AI in the smart parking area/mall parking area is used to give a consolidated report on slots available to reduce the latency to display the free slots. We propose to implement Smart Parking System based on IoT and Edge -AI to predict the possibility of getting the slot based on conditions such as weekdays, weekends, festive days, offer days.

Keywords: Automation, Image processing, Internet of Things, Edge-AI, KIOSK Machines, servo motors and mechanical structures, identify and sort various objects, Object Recognition algorithms, properties, and embedded systems.

Abstract: One third of the food produced 1.3 billion tons of food goes waste. In 2014 post -harvest losses in India were Reportedly around INR 9261st billion. Despite the fact that this understates. India’s annual food loss and waste, the country is ranked 94 th out of 107 on the Global Hunger, World Index, an 2020. Food waste is Intact energy Resources end up rotting away in landfalls. Which emits greenhouse gases in the environment heating atmosphere thus leafing to climate change. Wastage of food in such a negligence massive scale results un the part of individual, society and nation: and from different sources, Food wastage also effect the environment and economic conditions of the country

Keywords: - Food waste Management, Food wastage, Global food security, Environment, Economic conditions.

Abstract: Rabies is an illness that may spread from animals to people and is brought on by a virus. The rabies virus invades the mammalian nervous system. When biting or scratching someone, a rabid animal will mostly spread the disease through its saliva. The classical rabies virus still causes human rabies, which is nearly always deadly and for which no particular therapy is available anywhere in the world. To prevent dogs from getting infected with Rabies, When the dog is three months old, it receives its initial anti-rabies shot. The dog should visit the veterinarian annually for a booster shot. In this study, we discuss how microchip technology may be utilized to capture data on Bangalore's immunized street dogs and save it in our application's database, "VACCIDOG." The data on our application will assist offer an overview of street dogs that have had vaccinations. It will also cross-verify the vaccination information of a specific dog from a certain street with the aid of the distinctive ID supplied by the microchip. This paper is a conceptual paper and the data required was collected through secondary sources only i.e., by the way of Review of Literature and by the opinions of the authors.

Abstract: PowerPoint is a Microsoft Office application created for producing slideshows and presentations. Although many applications and online tools are competing with it, it is widely used around the world in different fields. Microsoft continues to enhance PowerPoint with many features to develop its use and keep it up to date with the fast-growing requirements by lecturers and presenters. In this paper, we will present the advanced features and tools in Microsoft PowerPoint 365. We will show how PowerPoint can be used not only in creating presentation, but also documents, videos and in graphic design.

Keywords: PowerPoint, Slideshow, Presentation, Microsoft Office.

Abstract: In the present work, the design of the river garbage collecting is the main focus. Currently, trillions of bits of plastic pollute the ocean, rivers, lakes, and seas, killing marine life, destroying ecosystems, and causing a mess on beaches. Hence, removing the plastic from the water is crucial, but no one is sure of the best way to go about it. In order to deliver the goods more quickly, nearly the entire assembly process is automated today. In large-scale production, automation is crucial.  Water environmental contamination results from floating materials on the water surface for an extended period of time, such as aquatic plants, plastic bottles, and bags. These floating objects typically do not disintegrate naturally or decompose slowly. By putting cameras on the riverside, the government management agency keeps an eye on the floating objects in the river in real time. To overcome this issue, we are creating a remotely operated waterway cleaning machine for this project. Our project's main goal is to gather all unwanted waste that is discovered floating on bodies of water while minimising labour requirements. We propose a river cleaning machine that will remove all floating waste particles from the river body. It is made up of two infrared sensors that detect waste particles and an ultrasonic sensor that detects the distance between the particle and the sensor. When the particles are detected, the machine moves towards them and collects the waste with the conveyor belt. This waste is collected in the machine's waste basket.

Keywords: Arduino uno, Ultrasonic sensor, IR sensor

Abstract: Previously, patient records were stored in physical form which led to issues such as limited storage space, difficulty in locating records for elderly patients, and vulnerability to damage or destruction. To address these issues, e-health cloud solutions have been introduced as a secure and accessible way of storing patient reports. Data is crucial in making informed decisions and providing optimal patient care. Cloud computing provides a cost-effective means of collecting, storing, and sharing data in real-time among healthcare organizations. However, the security and privacy of patient data are major concerns when using cloud-based healthcare services. Encryption is an essential security measure, which should be easy to implement, provide high protection without compromising network performance, and serve as an additional layer of security to safeguard customers data. Our focus is on data encryption in the healthcare cloud, which is the primary security concern in cloud computing. Authentication is the first step in data security and traditional authentication methods in cloud computing are insufficient to protect against advanced security threats. A dynamic approach to user authentication, which involves multiple authentication credentials, such as OTP, is necessary to enhance security. We propose a data security architecture that integrates a robust and viable multi-factor authentication scheme to ensure the security and privacy of patient data in the healthcare cloud

Keywords: AES; Cloud; Encryption; Decryption

Abstract: The Smart Traffic Management System is an advanced traffic management solution that utilizes modern technologies to enhance traffic flow and safety on the roads. The system incorporates several components such as an IR-based traffic density detection system, an RFID-based no parking system, an RFID-based emergency vehicle management system, and a speed breaker system using servo motors. The IR-based traffic density detection system helps to monitor and regulate the flow of vehicles on the roads, reducing congestion and improving safety. The RFID-based no parking system alerts drivers when they park their vehicles in prohibited areas, improving the management of parking spaces. The RFID-based emergency vehicle management system enables faster response times for emergency vehicles by automatically detecting and signalling their presence to other vehicles on the road. Finally, the speed breaker system using servo motors helps to slow down vehicles in high-risk areas, reducing accidents and increasing safety. Overall, the Smart Traffic Management System is an innovative solution that aims to optimize traffic management and safety, offering a range of benefits to drivers, pedestrians, and the environment.

Keywords: RFID Tag, Servo Motor, Density Based, Emergency Vehicle, Modern technologies

Abstract: The use of traditional methods for ringing bells in schools and colleges is still prevalent in modern times. However, this paper proposes a more efficient and automated solution in the form of an IoT-based automatic college bell system. The system utilizes NodeMCU as the primary controller and a set of sensors to detect the current time and trigger the bells to ring. This eliminates the potential for errors and delays associated with manual bell ringing. The system is highly reliable and customizable, thanks to its IoT technology, which allows users to program the ringing times and frequencies according to their specific needs. The RTC module tracks the time accurately, and the NodeMCU controller sends signals to the relay module to trigger the bells. By automating the bell-ringing process, educational institutions can enjoy a more efficient and flexible solution for their bell ringing needs.

Keywords: schools, colleges, efficient, automated solution, IoT-based, automatic college bell system, NodeMCU.

Abstract: Biometrics has developed to be one of the most relevant technologies used in Information Technology (IT) security. Uni - Biometric systems have issues such as noisy data, non-universality, spoof attacks and unacceptable error rate. These issues can be solved by making use of multimodal biometric systems. Multimodal biometric systems utilize two or more individual traits, like face, iris, retina and fingerprint. It has higher recognition accuracy than uni-modal methods. In this system, two uni-modal biometrics, fingerprint and face are used as multi-biometrics. Decision-level fusion of these two modalities can enhance the overall performance of biometric systems. In this context, the aim of this paper is to provide a comprehensive review of the state-of-the-art methods and techniques for face and fingerprint decision-level fusion. The paper discusses the challenges and benefits of fusing these two modalities, along with a critical analysis of the existing methods. Various decision-level fusion approaches, including score-level fusion, feature-level fusion, and classifier-level fusion, are described in detail. The paper also discusses the performance evaluation of face and fingerprint decision-level fusion systems and provides insights into the future research directions in this area. The findings of this review suggest that decision-level fusion of face and fingerprint biometric modalities is a promising approach for enhancing the overall performance of biometric systems.

Keywords: Fingerprint-recognition, Face-recognition, Multimodal Biometrics, Python, OpenCV

Abstract: Stock request vaticination, In this we can prognosticate the price of the stock on the base of the old information and current trend information we're collected. It uses the statistical analysis system and machine literacy using python. There are numerous factor which effects on the stock request like company profit report, profitable pointers, political events etc. Machine literacy is effectively enforced in soothsaying stock prices. The ideal is to prognosticate the stock prices in order to make further informed and accurate investment opinions.

Keywords: Prophetic analytics, Abecedarian analysis, Machine literacy, Artificial intelligence, Trading strategies, request pointers

Abstract: The objective of this paper is to introduce an environmental monitoring system that employs LoRa technology for wireless communication in IoT-based applications. The system is specifically designed to gather environmental data such as temperature and humidity from rural areas and transmit it to a central server for analysis and visualization. The system comprises three major components, namely, sensor nodes, a LoRa gateway, and a cloud-based server. Sensor nodes are installed at specific locations and equipped with sensors to collect environmental data. The data is transmitted wirelessly to the LoRa gateway through LoRa technology. Acting as an intermediary between the sensor nodes and the cloud-based server, the LoRa gateway receives and forwards the collected data to the server over the internet. Once the data reaches the cloud-based server, it is processed and analyzed. The proposed system offers several advantages, such as low power consumption, long-range wireless communication, and support for a large number of devices, and it can be used in various applications.

Keywords: Battery, TP4056, Solar Panel, ESP8266, DHT11, LoRa SX1278, OLED Display, IoT.

Abstract: In recent years smuggling at forest is a big problem. Robbers try to theft expensive trees like sandalwood, Teak wood etc. This incurrs a huge loss to government and it is difficult to monitor by forest officers. So that the proposed system with wireless sensor network to find the trees smuggling by using vibration and sound sensor. Each trees will be attached with a sensor which turns on alarm if someone is trying to cut the trees. In recent years forest destroyed due to natural fire, Example Amazon forest fire accident. The loss is in million and also the pollution is huge. Hence, The proposed a sensor based fire detection and automatic extinguisher (automatic water spraying unit)is designed to prevent the fire occurrence at the forest.

Keywords: IoT, GSM, LCD, Arduino.

Abstract: These days there have been rising cases in road accidents involving e- vehicles, street animals and pedestrians. This is mainly due to the fact that e-vehicles are not able to produce sounds on their own as conventional vehicles do. So we have taken this problem statement and decided to make a module that can replicate the sound and vibrations.The aim is to build a device that can be easily installed on an e-vehicle and has the ability to imitate both the sound and vibration of the conventional vehicle at different speeds. Hence resulting in safer roads. A sound and vibration of the conventional vehicle is sampled at different speeds and the sound will be sampled using a mic kept at a distance from the vehicle. The vibration can be measured using an accelerometer. Sound can be produced using a pair of Stereo speakers and the vibrations can be replicated using a motor. Implement an independent module that can be installed in an electric vehicle that will add the sound and vibration compatibility as that of the conventional vehicle. In order to trace the live path GSM/GPRS module is used.

Keywords: Sound , Vibration , Arduino Uno , GSM Module , GPS Module , SD Card, Speaker , Smartphone, mbedded C , LCD Display.HTML,CSS,PHP.

Abstract: To boost plant growth and output, farmers need automated disease monitoring of plants rather than human monitoring. Many plant diseases have the potential to cause significant losses or possibly no harvest. Anthraconose, bacterial blight, cercospora leaf spot, and healthy leaves were the subjects of this study's focus on several alterneria alternata diseases. We apply three stages of clustering on the initial image filtering. As a result, we developed a modern technique in this study to detect diseases linked to both leaves and fruits. We overcame the shortcomings of the conventional eye monitoring method by using a digital image processing methodology for rapid and accurate plant disease identification.

Keywords: Convolutional Neural Network (CNN), Support Vector Machine (SVM), Confusion matrix

Abstract: Water scarcity is a significant problem that many nations worldwide are dealing with. A mechanism for monitoring water levels has been created to prevent water waste. This system wirelessly communicates water level information to registered users while autonomously detecting and signalling water levels in reservoirs, overhead tanks, and other storage containers. People could desire to automate their chores in order to conserve energy and increase productivity. Water levels are frequently checked with ultrasonic sensors, which use high-frequency ultrasonic vibrations to detect the level of liquids or solids. These sensors are installed at the top of a tank and send out waves while simultaneously timing how long it takes the sensor to receive the return signal. For the internal study of water dams, household/society water tanks, and municipal water towers, the suggested solution proposes to use a webserver. It can be difficult and time-consuming to check the water level in these containers. The project also aims to solve the problem of water waste. When the tank is full, individuals frequently fail to turn off the motor, wasting water. The water level monitoring device may be used to keep an eye on water usage and levels, which will help cut down on water waste. A water level indicator is used to find and show the water level in an overhead tank or any other water container. In this work, we outline the NodeMCU-based design of a water level sensor device. A water sensor detects the water level, an ultrasonic sensor produces ultrasonic waves, LEDs display the water level, and a computer monitors the water levels. The level of any liquid in any application can be monitored with this highly effective circuit.

Keywords: LoRa SX1278, UITRASONIC SENSOR, ESP8266, TP4056, OLED DISPLAY, Li-ion BATTERY, SOLAR PANEL  

Abstract: The paper presents a novel algorithm called Modified End-to-End Secure Low Energy Adaptive Clustering Hierarchy (ME-LEACH) for extending the lifetime of Wireless Sensor Networks (WSNs). Energy constraints are a significant challenge in WSNs, and thus, efficient energy usage is essential for all activities within a WSN. Existing protocols have been introduced to address energy dissipation issues, such as the End-to-End Secure Low Energy Adaptive Clustering Hierarchy (E-LEACH) protocol, which is a hierarchical routing algorithm. However, E-LEACH suffers from high energy consumption as each Cluster Head (CH) directly sends data to the base station. In the proposed ME-LEACH method, a CH identifies the nearest CH and uses it as the next hop, forming a chain of CHs that serve as a path to the base station or sink. This approach aims to improve energy efficiency in WSNs and reduce energy dissipation during data transmission. The widespread applications of WSNs in various fields of science and technology highlight the significance of this research.

Keywords: LEACH, Wireless Sensor Network, WSN, Cluster Head 

Abstract: This project involves the creation of a Bluetooth-controlled turret gun using 3D printed parts and an Arduino. The system can be remotely controlled using a smartphone or a computer, making it ideal for use in various applications, including security systems, gaming, and entertainment. The design is highly customizable and can be adapted to suit different requirements. The main components of the system include a 3D printed turret, servo motors, a Bluetooth module, and an Arduino board. The servo motors enable the turret to rotate and move up and down, while the Bluetooth module facilitates wireless communication with the controlling device. The Arduino board acts as the brain of the system, processing the commands received from the Bluetooth module and sending the appropriate signals to the servo motors. Overall, this project provides an exciting opportunity to explore the potential of 3D printing and Arduino technology in the development of innovative and highly functional devices.

Keywords: Bluetooth Technology, 3D printing, Arduino, Wireless communication, Arduino IDE, Bluetooth-controlled turret gun.

Abstract: These days, instead of using local storage devices, cloud storage is used to store and retrieve data. Cloud storage is based on the internet and provides data that is more dependable, safe, and readily available. Nonetheless, the information is crucial and shouldn't be shared with anyone not authorised. On the cloud, there is a lot of data that needs to be secured against unauthorised access. A variety of algorithms are employed to protect the security and privacy of data. Every system aims to achieve availability, confidentiality, and integrity (CIA). Nevertheless, these CIA features are not offered by the current centralised cloud storage. Decentralized cloud storage and blockchain technology are thus utilised to increase the security of data and storing methods. It efficiently aids in preventing data from being altered or having a portion of it deleted. A chain of blocks connects the data contained in blockchain to one another. Each block has a hash value that is saved in the following block. Consequently, it lessens the likelihood of data alteration. The SHA-3 Hashing algorithm is employed for this.

Keywords: Web 3.0, Blockchain, DApp, SHA 3, Two fish, Ethereum, Decentralization.

Abstract: A Network intrusion detection system (NIDS) is a security technology that monitors network traffic for suspicious activity and alerts administrators or security personnel when potential threats are detected. The primary goal of a NIDS is to identify and respond to malicious activities such as unauthorized access, data theft, and other cyber-attacks. NIDS can be implemented using a variety of techniques, including signature-based detection, anomaly detection, and machine learning. By analysing network traffic in real-time, NIDS can provide an effective defence against cyber threats and help organizations protect their valuable assets from unauthorized access and data breaches. This abstract provides an overview of NIDS and its importance in network security.

Keywords: Autoencoder, Machine Learning, Ensemble Model

Abstract: The Online Bus Booking and tracking system is a web-based application designed to streamline the Bus Booking Process and Provide a bassle-free travel experience for users. The system features a user-friendly interface, secure payment gateway, and a real-time bus Tracking system powered by GPS technology. Overall, the Online Bus Booking and Tracking System aims to provide a seamless and convenient travel experience for users, leveraging modern technologies to simplify the booking process and ensure a safe and comfortable journey.

Keywords: Convenience, Efficiency, Real-time tracking, Security, Scalability

Abstract: Recognizing human activity is important for interpersonal interactions and human-to-human communication. Since it provides information on a person's identity, personality, and psychological condition, it is difficult to extract. Multiple activity detection systems are now required in a variety of applications, including robotics for defining human behaviour, human-computer interaction, and video surveillance systems. To do this, we'll combine the OpenCV model with the ML algorithm(like CNN). The developed model will finally be integrated with a website that will use the webcam and provide the result of the activity being performed accurately.

Keywords: Convolutional Neural Network (CNN) ,Human activities recognition (HAR)

Abstract: High-Speed rail(HSR) communication has always been an attractive research topic with the continuous progress of transportation systems and communication technologies. Recently, Hyperloop has emerged as a candidate for very high-speed transportation systems. Because of its outstanding potential, Hyperloop can usher in a new transportation era with several attractive features. Developing suitable communication system solutions is crucial to bring this promising technology closer to reality. The Hyperloop communication system is essential to support monitoring-and-controlling services and deliver communication services inside its capsules/pods. It must be studied to determine if existing HSR communication technologies can establish robust communication links and deliver data with the required QoS.

Keywords: HSR, Hyperloop, transportation, communication technologies, monitoring, controlling, QoS.

Abstract: In the past, detecting fruit diseases relied on human visual inspection, which was often unreliable due to subjective judgment and limitations in detecting microorganisms. This approach was time-consuming, costly, and less accurate. However, using MATLAB-based approaches for quick and accurate diagnosis is a better choice compared to outdated methods. Symptoms of infection or disease can manifest on fruits, leaves, and lesions of plants, and this project aims to accurately diagnose the condition based on submitted images through image segmentation, preprocessing, feature extraction, and labeling. Various factors such as insect transmission, weather, and environmental conditions can cause infectious diseases in fruits, caused by viruses, fungi, or bacteria. The project will focus on identifying the cause of contamination in fruits to determine the type of infection, by extracting major and minor axes of fruit characteristics from images for effective classification.

Keywords: K-Means Clustering, Local Binary Pattern, Multi-class Support Vector Machine, Texture Classification

Abstract: This paper presents system based on pose detection for yoga pose recognition. Yoga, which has its roots in India, is a form of physical activity that helps your body and mind work together properly for each of their individual functions. In many nations around the world, yoga of Indian heritage is primarily used to maintain health. As a result, the body's posture while practising yoga has a significant impact on one's health. Many medical professionals advised doing yoga to help patients recover from injuries more quickly and as the greatest way to combat mental health issues like depression, anxiety, and post-traumatic stress. Some yoga practitioners don't do their yoga postures correctly, which causes a variety of physical issues such joint discomfort, disc difficulties, shoulder pain, etc. We are launching a tool for categorising and improving your yoga. It will use MoveNet as a classification model to examine your yoga-related bodily motions.

Keywords: Non-Parametric Weight Feature Extraction (NFWE), Principal Component Analysis (PCA), TensorFlow, MoveNet, 17-Keypoints.

Abstract: High- Energy is the key input to drive the improve the life cycle. The consumption of the energy is directly proportional to the progress of the mankind with ever growing population, improvement in the living standard of the humanity, industrialization of the developing countries like India. The global demand for energy is increasing on alarming rate. The primary source of energy is fossil fuel (like coal, diesel), which are decreasing day by day due to move energy demand and there is global warming problem due to these sources. So, we need non-conventional energy sources to full fill the demand of energy .Recent improvements in the power conversion efficiencies of organic solar cells have broughrenewed attention to possibility of practical large-scale use of these devices. This paper deals with basic principal of operation of plastic solar cells and we demonstrate the implementation of the nanorod and screen printing technology in the fabrication of organic-based heterojunction solar cells.

Keywords: Polymer, Solar energy, Nanotechnology, Screen printing technology.

Abstract: Virtualization & Cloud computing are two popular research directions in recent times. Today, Virtualization is being used by a growing number of organizations to reduce power consumption, Server Consolidation, Testing and Development, Dynamic Load Balancing & Disaster Recovery, Virtual Desktops and Improved System Reliability & Security. Virtualization also provides high availability for critical applications, and streamlines application deployment and migrations. Through cloud computing, Information Technology resources can be delivered as services over the Internet to the end user. Virtualization is one of such important core technologies of cloud computing.

Keywords: Cloud Application, Virtualization, Testing and Development, cloud computing.

Abstract: This work entails developing a device for extracting sugarcane juice. The operator of a sugarcane juice machine of the past had to rely solely on his hands, leaving his legs dormant while he stood to do his work. Therefore, we update the sugarcane mill with some modern features. Machine parts include a pulley, a v-belt, a flywheel, a rotor made of cast iron, bearings, a pedal, and a body frame. The sugarcane machine has been modified so that the operator can use their legs to pedal instead of their hands. By using a flywheel to ensure continuous rotation, we are able to solve the problem of vibration and shocks. Keyword: Pulley, V-Belt, Flywheel, Cast Iron Rotor, Bearings And Pedal With Body Frame

Abstract: The vision of this application is to provide a platform which will help farmers from Indian villages to sell their products to different cities. It will make easy for farmers to sell their products without much effort. This application will provide a huge and accurate information for farmers as well as consumers, in terms of maybe reasonable prices of products sold, ensuring good quality crops / products, schemes provided by governments regarding for the welfare of farmers. It will provide the list of items with its favourable or reasonable costs including each and every tax factors. It will also reduce the main huge chain between farmers and consumers such as transportation costs, wholesaler market costs, etc. It will also show details of each government policies announced for farmers.

Keywords: Mobile Application, Farmers, Consumers, Agricultural Product, KVK Verification

Keywords: IoT, Smart connectivity, Energy efficiency, Evaporative cooling technology, Remote control, Humidity control, Smart sensors.

Abstract: To overcome the problem of overbilling, Meter tampering and to ensure a cost-effective operation, this project aims to design a power monitoring system. In this system the microcontroller is used to detect the power theft and passes the information to electricity board with the help of an IOT application. The whole network uses LCD, current sensors, energy meter, microcontroller, IOT module, PCB board, alarm, relay, voltage regulator. Relay is used as a switch to disconnect the load and to stop the theft.

Keywords: Electricity Thefts, Monitoring System, Meter Tampering.

Abstract: This project focuses on monitoring the voltage of AC-powered equipment and developing an automated temperature ventilation system to regulate the temperature of a space and protect appliances from overheating. The Node MCU microcontroller and IP networking are used for remote access and control, allowing users to automate various electrical appliances such as lamps, fans, lights, and refrigerators through an Android smartphone app even when they are not physically present. This technology is particularly valuable in environments where temperature control is critical. The proposed voltage control scheme has been tested with AC lamps, AC fans, and DC cooling fans to assess its feasibility and effectiveness. With the increasing use of the Internet of Things (IoT), this technology is becoming more sophisticated and widely utilized. In real-world scenarios, electricity usage data can be calculated by the electricity board and sent to users via email or EB card for billing purposes.

Keywords: IoT, Microcontroller, Voltage Control, Temperature Sensor, Current sensor

Abstract: The need for computer-aided medical diagnostics has grown in recent years as the population's need for medical care has risen. Because to advancements in imaging technology, Computed Tomography (CT) image-based diagnosis has become commonplace due to its cheap cost, reliability, and non-invasive nature. Images of the anomaly, such as a tumour, cyst, stone, etc., are analysed using feature extraction, analysis, and pattern recognition methods to locate the problem. The imaging technique of kidney-urinary-belly computed tomography (KUB CT) has the power to enhance kidney stone screening. As the population's need for medical care has increased, so has the demand for computer-aided medical diagnostics. Computed Tomography (CT) image-based diagnosis has grown widespread as a result of advances in imaging technology because of its low cost, dependability, and non-invasive nature. In order to identify the issue, feature extraction, analysis, and pattern recognition algorithms are used to analyse images of the anomaly, such as a tumour, cyst, stone, etc. The imaging method known as kidney-urinary-belly computed tomography (KUB CT) has the potential to improve the detection and prognosis of kidney stones. This study (CLAHE) focuses on effective computer-assisted medical diagnosis using KUB CT kidney images using contrast-limited adaptive diagram equal sign. Success depends on many factors, including segmentation, feature selection, reference database size, computational performance, etc.

Keywords: kidney stones, computed tomography, image processing

Abstract: In recent years there has been a vast technological improvement in industrial control rooms for monitoring the entire field of Industrial plants. High-end microcontrollers are being implemented for controlling the entire process of fields. But a problem is that even though automation takes complete control of total plants few authentication and manual actions are needed from the user side to complete the control action. Hence there is a must situation for users present at all times in the control room to take some time needed control actions. Due to the static nature of the control room environment, the user should always be static to monitor the process. In this project, we propose a system that promotes the control engineer to obtain the data values anywhere and everywhere within the control room. This new system is suited for acquiring the control parameters. The main objective of this proposed work is to acquire sensor data and store it in the Data Acquisition Cloud which can be accessed from the Android App specially designed for this purpose.

Keywords: IoT, Light Sensor, Humidity Sensor, Temperature Sensor, Gas Sensor, ESP32 Microcontroller

Abstract: One of the more recent developments to develop a distinct identity is blockchain. This technology has the potential to significantly affect HR. It has an extensive number of fields besides HR in which it has already shown to be extremely significant. It is a decentralised and distributed form of a ledger that may store various kinds of information, including data regarding loans, ownership rights, data connected to the transaction of any asset, etc., in addition to business transactions. Because it is decentralized, it can be accessed from a variety of networks yet cannot be altered, making it extremely transparent and even secure. The paper has made an attempt to describe the numerous industries in which blockchain technology is employed and, more importantly, the features and advantages of blockchain technology that make it so crucial for organisations' human resources management departments. Key word: Bitcoin, blockchain, cryptography, Human Resource Management

Abstract: The most challenging terrains can be traversed by all-terrain electric vehicles. The low cost of ownership of electric ATVs and UTVS, an increase in the use of ATVs for military and recreational purposes, and growing public awareness of the need to reduce greenhouse gas emissions are all likely to contribute to the growth of the global market for electric all-terrain vehicles (ATVs). The expanding range of applications for electric ATV is influenced by rising EV safety standards, rising consumer demand for a better driving experience, and EVs' cheap maintenance costs. Therefore, our objective is to design and construct an effective, reliable, safe, and powerful electric ATV as well as to provide a versatile data collecting and telemetry system for EVs.

Keywords: eVCU, Electronic Control Unit, Formula car control system

Abstract: A general winding design rule for the pole- phase modulation (PPM) induction machine is proposed, and three different structures, analogous as conventional winding machine, toroidal winding machine, and double- rotor toroidal winding machine, are compared. The results corroborate advantages of the conventional winding machine over the others in operation to the PPM. A steady model for the conventional winding- predicated PPM induction machine, including inductance matrices, voltages, flux liaison, mechanical dynamics, and choker equation, are deduced by employing the winding distributed function. A prototype validates the feasibility of the designed pole- changing winding and the erected model, which is suitable for operation in different poles, singly; also, it illustrates effective operation in the pole- changing process, where both operating modes attend. Double vector control algorithms are developed to control the PPM induction machine for different poles, singly, with their different parameters and the given rotor flux liaison. also, only four current sensors are demanded, indeed however there are nine winding currents; the choker share function ensures a constant choker during pole changing. The simulated and experimental results corroborate the proposed winding design, model, and control system of the PPM induction machine drive

Keywords: Induction machines, magnetic analysis, pole changing, pole-phase modulation, vector control.

Abstract: Course-Hub is a web application which offers the courses to the user. In previous time students should learn the courses in multiple different platforms, so it becomes difficult for the user those who are using the web to learn. Reading the reviews given by different people who have already used the courses will reduce the stress to a great extent.

Classification among the courses which one is good or which one to choose is a big problem for the students which will be reduced by using our platform, as it has review and feedback system for the users. Also, there are many courses which are not up to the mark which just waste the time of students leading in losing the interest in particular topic, here we have selected and best courses for the purpose.  It is a type of a e-learning application

Keywords: e-learning – Electronic Learning, feedback system, courses

Abstract: A system based on an Android application has gained great popularity for making people's lives easier. Since mobile platforms have become more user-friendly, computationally powerful, and affordable, innovations in mobile software applications can be beneficial to public health. We have developed and evaluated application that facilitates the connection between doctors and patients. A user-friendly interface has been developed to make this system efficient and user-friendly, providing the doctor with previous detailed patient information that is stored permanently in the database, making it easy for the doctor to review previous prescriptions of the specific patient when they encounter any problems. After successful registration and login, the patient can book an appointment and view prescribed medicines by the doctor and past lab records. The purpose of this application is to record patient information in a digital format for future reference.

Keywords: Smart health, mobile healthcare, web application, Android application.

Abstract: Deep learning has been effectively used to address a variety of challenging issues, from computer vision to big data analytics. Advances in deep learning have also been used to develop software that poses risks to national security, privacy, and democracy. Deepfake is one of those recently developed deep learning-based applications. The recent entry of deepfakes has marked a turning point in the development of fake material, even if manipulations of visual and auditory media are as old as media itself. Deepfakes offer automated methods for producing fake content that is getting more difficult for human observers to spot thanks to the most recent developments in artificial intelligence and machine learning. Therefore, the development of systems that can instantly identify and evaluate the integrity of digital visual media is essential. The discipline of computer vision, a branch of computer science, has developed methods for producing and identifying deepfakes. Humanities and social science approaches have focused on the social and ethical ramifications of deepfakes. This study examines the algorithms used to produce deep fakes.

Keywords: Deepfakes, Generation and Detection of Deepfake, Generative Adversarial Network, Autoencoders.  

Abstract: Technologies like AI ,machine learning, data science are becoming upgraded. The advancement in available, portable, low cost handheld devices like cell phones and availability of network connection has resulted within the user’s mobility at an unprecedented level. We've studied different methodologies like Smart goal annotation, state phase annotation, collection process, agreement results also as annotation skills for achieving the health goals. The user has got to type their health regarding the query based on that assistant giving the acceptable answer. The facilities like report generation and scheduling assignment are provided. It'll increase the interaction between humans and machines with the assistance of different technologies, vast dialogue ,conversational knowledge based, public knowledge based. The system uses different algorithms for disease recognition, behavior abnormality detection, prediction etc. Experimental results show that: Compared with traditional methods,the proposed method is more accurate and faster and patients can get service anywhere and anytime.

Keywords: Conversational Interface, Machine Learning, NLP Algorithm, Patient health monitoring, SVM Algorithm.

Abstract: This project involves the use of K-Means Clustering to find the best accommodation for the students in Nagpur by classifying accommodation for incoming students on the basis of their preferences on amenity, budget and proximity to the location.

Keywords: Data, K-Means, Recommendations, Map

Abstract: This research study is devoted to the investigation of deep neural networks (DNN) for classification of the complex problem of knee osteoarthritis diagnosis. Osteoarthritis (OA) is the most common chronic condition of the joints revealing a variation in symptoms’ intensity, frequency and pattern. A large number of features/factors need to be assessed for knee OA, mainly related with medical risks factors including advanced age, gender, hormonal status, body weight or size, family history of disease etc. The main goal of this research study is to implement deep neural networks as a new efficient machine learning approach for this classification task taking into account the large number of medical factors affecting OA. The potential of the proposed methodology was demonstrated by classifying different subgroups of control participants from self-reported clinical data and providing a category of knee OA diagnosis. The investigated subgroups were defined by gender, age and obesity. Furthermore, to validate the proposed deep learning methodology, a comparison analysis between the proposed DNN and some benchmark machine learning techniques recommended for classification was conducted and the results showed the effectiveness of deep learning in the diagnosis of knee OA.

Keywords: data classification, machine learning, deep learning, osteoarthritis

Abstract: A movies recommendation chatbot is an essential component of developing an effective and reliable platform for users. The chatbot should be able to provide impressive movie recommendations depending on user preferences, such as genre, year of release, language, director, actor/actress, rating and other variables. The abstract should detail the specific features of the chatbot that make it unique and more convenient than other movie recommendation platforms. Integration with various databases such as IMDB will aid in providing accurate and sufficient recommendations without causing delays by taking advantage of state-of-the-art machine learning algorithms ensuring quality service delivery. Incorporating human-like dialogue structure and suggestions built on past movies recommended can further improve user satisfaction levels. By providing comprehensive information in the abstract about a movie recommendation chatbot's design and functionality, developers can ensure more successful implementation while allowing audiences to have tailored entertainment options readily available at their fingertips.

Keywords: Movie recommendation, Language preferences, IMDB integration, Machine learning algorithms, User feedback, User history, similar movies, User-friendly interface etc.

Abstract: Machine Learning has several category of algorithms that allows software applications to be more accurate in predicting results without being explicitly programmed. In this paper, the case of Big Mart, a one-stop-shopping center, has been discussed to predict the sales of different attributes, item varieties and for understanding the effects of different factors on the items’ sales. Considering various aspects of a dataset collected for Big Mart, methodology followed for constructing a predictive model, highly accurate results are generated, and these observations can be employed to take decisions to improve sales.

Keywords:  Machine Learning, Sales Prediction, XGBoost Algorithm, Random Forest Algorithm, Linear Regression algorithm.

Abstract: Breast cancer is one of the most common forms of cancer in women worldwide, and early detection is crucial to successful treatment. However, accurately diagnosing breast cancer can be challenging, and there is often a need for more effective methods for detecting and diagnosing the disease. This project aims to generate rules from the Breast Cancer Wisconsin dataset using a combination of data exploration, feature reduction, and machine learning algorithms. The first step is to explore and understand the dataset, followed by rule conversion using random forest. Feature reduction is then performed using Extra Tree Classifier, RFE, and correlation between features, and the top 10 features are selected. Then SelectFromModel method is used to further reduce the features to 5. Rule conversion is performed again using random forest on the selected features. Finally, the generated rules are predicted with the original dataset using several machine learning algorithms such as SVM, MLP, Gradient Booster, Ada Booster, CNN, Extra Tree, and Logistic Regression. By identifying the most important features for predicting breast cancer, we aim to provide clinicians and researchers with valuable insights and tools for more accurate diagnosis and treatment of the disease.

Keywords: Breast cancer, Rule generation, Random forest, Feature selection, ExtraTreeClassifier, RFE Correlation, SVM, MLP , Gradient boosting , AdaBoost ,CNN , Logistic regression

Abstract: In present situation human being is facing many health issues, these problems must be exactly examine without any compromising. In the condition of contrary disorder, the common procedure of analysis might not be tolerable. Diagnosis of disease in early stage of any health issues is significant; as the disease determines earlier may result is more effective treatment or extensive persistence time. In the past decade, the operation of particular disease prediction implement combined with the regarding health has been magnified because of a range of disease and fewer doctor- patient magnitude relation. Prediction of disease with an accuracy can be done through by using machine learning algorithms like CNN, SVM, Random forest algorithm etc but VGG16 will give more accuracy compare to other algorithm. This paper, we are using VGG16 for more accuracy of above 90%. The system has unbelievable potential in forestalling the possible diseases more exactly.

Keywords: VGG16 (Visual Group Geometry), Covid-19, viral pneumonia, brain tumour, Kidney Stone

Abstract: A music recommendation system was developed that can learn users' preferences. The system can classify a wide range of stored music using automatic music content analyses. Users can opt for music according to their mood, using such words as "bright", "exciting", "quiet", and "sad". Building a music recommendation system is one of the information retrieval tasks. This research is devoted to a content-based music recommender system. The main peculiarity of our work is that the developed recommender system is based on the acoustic similarity of musical compositions. Two approaches to building a content-based music recommender system are considered in this paper. The first is a quite common approach that uses acoustic features analysis. The second approach includes deep learning and computer vision methods applications aimed at improving the results of the recommender system. Keywords: Numpy, Pandas, Cosine Similarity, Count Vectorizer

Keywords: Visual Foundation model, AI, Large Language Models (LLM).

Keywords: Pipeline inspection, Crack detection and Blockage clearance.

Abstract: The entire economy of the country is working towards achieving the goal of sustainability by adopting green and sustainable practices. Each sector of the economy is contributing in its own way in order to achieve the aforementioned goal including business industries. Corporates are working toward incorporating green and sustainable practices in each of their processes and departments in order to achieve organizational sustainability and maintain their goodwill in the market. One of the departments or processes in corporate that has included these green practices is the Human Resource Management department as human resource plays a key role in achieving organizational sustainability. This paper will highlight the importance of the concept of Green Human Resources in achieving organizational sustainability. This paper is a conceptual paper and the data required was collected through secondary sources only i.e., by the way of Review of Literature and by the opinions of the authors.

Keywords: Human Resource, Green Human Resource Management, Organizational Sustainability

Keywords: dementia, android, reminder, dependency.

Abstract: Online reviews in modern businesses and e-commerce platforms are influential and this is an important factor for customers. Potential buyers heavily rely on user’s feedback when deciding whether or not to purchase products online. Unfortunately, there are some unscrupulous individuals and organizations that attempt to manipulate these reviews to suit their interests. As a result, fake reviews increase and mislead customers/buyers. To address this issue, a proposed solution involves the implementation of an e-commerce platform that utilizes an NLP algorithm to analyze the features and sentiments of reviews and a data science algorithm to classify any fraudulent text. The proposed system contains a review detection model within an e-commerce application, where customers may register, view products, and make purchases. As customers buy products, they post reviews and ratings. Using these inputs, the model is able to classify given reviews as false or true using KNN classification algorithm.

Keywords: Machine Learning, NLP, Fake Reviews, Classification Algorithm, KNN, Lesk

Abstract: As technology advances, data volume and velocity increase in all domains. Data is everywhere, which creates a data mess situation in many organizations. Sometimes, it makes challenging to think how this data can be utilized to work for the betterment of the organization without storing it in many places in different formats or duplicating it again and again. There comes the ‘Data Mesh’ design, which is a relatively new concept focusing on data storage, data governance, and data management in an efficient way to encourage self-service data handling. Many organizations are now considering this new “Data Mesh” concept to address the major issues and barriers in data management and usage. They realize that by focusing on domain-specific data products enabled by common support functions, they can ensure flexible access to data with the significant benefit of reduced time-to-market and fast-to-product development. The data Mesh incorporates contemporary architectural concepts and focuses on data management rather than connectivity and orchestration.

Keywords: data mess, data mesh, SSP, SLAO, sustainability

Abstract: Nowadays, misplacing valuables are very common, so tracking is becoming essential for the purpose of improving our life condition. In order to safeguard our valuables such as, wallets, keys, toddlers, animals and so on, we require some device which helps to locate these misplaced or stolen objects. So that a real-time object tracking system is implemented using Google Maps and Arduino with the integration of Global Positioning System (GPS) technology. The GPS module provides geographic coordinates of the object at regular intervals, and transmits the location information to the owner/user's cell phone in terms of latitude and longitude. The owner/user can continuously monitor the objects such as vehicles, animals, children, using their cell phone. The system is user-friendly, compact, ensuring safety and surveillance at a low maintenance cost. The experimental results of the proposed system show its feasibility and effectiveness in real-world scenarios.

Keywords: GPS; Cell phone; Arduino UNO; Android Studio.

Abstract: Low efficiency and complex services are issues in the present medical insurance claims procedure. A patient must visit the hospital to request a diagnosis certificate and receipt before sending the necessary application materials to the insurance provider in order to submit a medical insurance claim. The patient won't get paid until the business has finished verifying everything with the hospital. However, blockchain technology has the potential to make the situation better. The new project is an integrated healthcare system in which all the hospitals and insurance companies will be able to do registration in the system. The patient’s health record eg. medical bills, reports, admit cards, etc. will be maintained on blockchain servers in encrypted format and patient will be able to claim the insurance. The insurance company will be able to review all the bills and reports. As all data is maintained on blockchain servers there is no possibility of manipulation in bills and reports hence transparency will be maintained and security of the claims processing will be increased.

Keywords: Blockchain, Medical Insurance, Insurance claim, AES, SHA.

Abstract: Security breaches are very common where the safety of the users is put to threat. Hence it is necessary that a threat to the system is identified which can be done with the help of malware detection. In order to explore, infect, steal data or virtually behave as the attacker wants with the help of a file or code delivered through a network is known as a malware. A PE malware typically is a malware code which is propagated through a PE file downloaded on the device which may result in loss of information and replacement of such malicious codes. Such malware creators get away with it easily due to traditional methods of testing which are unreliable and time consuming. The current thesis aims to deploy a prototype that uses the concepts of feature extraction and use the Portable Executable file at a later stage. These features extracted are fed to algorithms based on ML (machine learning) and deep learning so that the overall system of the model is enhanced when the feature undergoes layers of neutral networks. The model undergoes pre-processing techniques which is then fed to algorithms for training.

Keywords: PE files, malware, machine learning, deep learning

Abstract: Digital data security is of utmost importance in today's world, both cryptography and steganography are important tools to ensure the confidentiality and integrity of the data. Cryptography involves transforming the plaintext into ciphertext using encryption techniques and then decrypting it back into plaintext using decryption techniques and steganography involves hiding data in plain sight by embedding it in cover media such as images, audio, or video. Both cryptography and steganography have their own strengths and weaknesses, they can be combined to provide even better protection for digital data. By encrypting the data before embedding it in cover media using steganography, we can ensure that even if the cover media is intercepted, the data remains secure as it is encrypted. Regarding audio steganography, the techniques you mentioned, such as LSB, Echo hiding, Phase coding, and Tone insertion, are commonly used. For example, LSB is a simple technique that involves replacing the least significant bits of audio samples with data bits, while Echo hiding involves modifying the echo of an audio signal to hide the data. The combination of cryptography and steganography can provide better protection for digital data. Audio steganography techniques such as LSB, Echo hiding, Phase coding, and Tone insertion can be used depending on the specific requirements of the application.

Keywords: Human auditory system, least significant bit, Peak signal-to-noise ratio, Rivest Cipher4, 3Data Encryption Algorithm.

Abstract: Azure is a cloud computing platform that offers the range of services to store, manage, and analyse data. In the healthcare platform, Azure can be used to store and manage the records securely and efficiently. This abstract mainly explores the use of Azure for healthcare records and how it can be benefit the healthcare industry. Azure offers robust security features, such as data encryption, access control, and threat detection, to protect patient’s information from unauthorized access or cyber threats. Azure’s scalability allows healthcare organization to easily manage and process large volumes of data as their patient base grows.

Keywords: Microsoft Azure, Vue, Docker, Node js, postgresql, Nginx, Typescript.

Abstract: Petroleum products are one of nature's unique and valuable creations, thus it is important to use and distribute them properly. The project's goal is to develop an RFID-based system that can automatically deduct the amount of petrol dispensed from the user card. The fuel systems are currently manually controlled. These petrol pumps are time-consuming and labour-intensive. Simply place the RFID card close to the RFID reader whenever we wish to fill the tank from the fuel dispenser. The microcontroller then reads the information from the RFID reader and executes the action in accordance with the demands of the consumer. By eliminating human intervention, this automated petrol pump system also offers customers security when filling up at petrol stations, lowering the risk of carrying cash constantly. When RFID reader reads the card, the system asks for the amount and it also shows the balance amount. On entering the amount, the motor starts and petrol gets filled in the petrol tank from the fuel dispenser.

Keywords: RFID, Microcontroller, Fuel Dispensing System, Automation.

Abstract: Day by day, the population of the country is increasing and the requirement of the power is also increasing. At the same time the wastage of energy is also increasing in many ways. So, reforming this energy back to usable form is the major solution. In this footstep power generation project, we are generating power with the help of human’s footsteps; this power is then used to charge battery. The power is stored in a battery that can be used to charge a mobile phone using RFID card. This system is powered by Atmega 328 microcontroller, it consists of Arduino IDE, RFID sensors, USB cable and LCD. When we power on the system, the system enters into registration mode. We can register three users. Once all the user is entered in the system then the system asks to swipe the card and connect the charger. Initially all the user is given by 5 minutes of charging time as default. When we swipe the card and if the user is authorized, the system turns on for charging and will charge the Mobile phone. If the user is un-authorized then the system will display as unauthorized user, just in case if the user wants to stop the charging in midway the user needs to swipe the card again. As soon as the card is swiped again, the remaining time balance is displayed and the charging stops. In order to recharge a card, we need to press recharge button which is on the system, and then system will ask to swipe the card, once the user swipes the card, it adda more 5 minutes to the particular card of the user.

Keywords: ATmega328P, Piezoelectric Sensor, LCD’s, Crystal Oscillator, Resistors, Capacitors, Transistors, Cables & Connectors, Transformer/Adapter, PCB.

Abstract: This research proposed an android-based-approach for the design of a mobile smartphone anti-theft system that is fit for performing Subscriber Identity Module (SIM) card discovery, location and mobility information fetching through Global Positioning System (GPS), sending the fetched location using Short Message Service (SMS), passing culprit’s mobility information to the corresponding mobile operator to provide the mobile number, capturing culprit pictures using either the camera of the stolen phone or the culprit image captured by the mobile operator and transferring the information to the alternate email id/SIM and appropriate authority to capture the smartphone theft culprit. The system was developed using Android Studio IDE, Java programming language, and SQLite database. The system evaluation was carried out using a survey form integrated into the developed anti-theft system. On average, more than 80% of the participants found the framework to be simple and easy to use.

Keywords: Smartphones; Anti-Theft System; Subscriber Identity Module; Global Positioning System; Short Message Service

Abstract: The fabrication of thin films Cu2S/CdS by cost affecting spray pyrolysis technique is demonstrated. Thin films of CdS were deposited onto antimony doped tin-oxide (ATO) substrate later Cu2S film was formed by dipping the alloy films in a heated solution of CuCl. The structural and morphological properties of these thin films were studied by recording X-ray diffraction patterns and atomic force microscope images. The X-ray diffraction pattern of Cu2S/CdS reveals the peaks due to both Cu2S and CdS materials and leads to the confirmation of Cu2S/CdS thin film formation over the ATO substrate. Further, the Cu2S/CdS thin film-based device was fabricated by forming top contact through complete metallization of the Cu2S with tin paste. The current-voltage (I-V) characteristics of Cu2S/CdS device reveals diode behavior under applying bias voltage across. Furthermore, the various diode parameters such as ideality factor, saturation current, barrier height, and series resistance were also estimated using different diode equations. The Cu2S/CdS device exhibits slightly Ohmic characteristics and attributed the presence of defect states at the Cu2S/CdS interface. Thus, this study may emerges out to be very fascinating for further fabrication of solar cells based on Cu2S/CdS thin films.

Keywords: Spray pyrolysis, CdS, Cu2S, XRD, I-V characteristics

Keywords: Cryptocurrency, Decentralized Exchanges, Centralized, Liquidity

Abstract: This project presents a modern approach for surveillance at remote and border areas using multifunctional robot based on current IOT technology used in defence and military applications. This robotic vehicle has ability to substitute the soldier at border areas to provide surveillance and services. The robotic vehicle works both as autonomous and manually controlled vehicle using internet as communication medium. This multi-sensory robot used to detect and diffuse the bombs, used to detect injured soldier and carry the injured person to base station, at remote and war field areas and to charge the equipment’s. Conventionally, wireless security robot is obsolete due to limited frequency range and limited manual control. These limitations are surmounted by using IOT technology which has limitless range. It can eliminate the need of deploying humans at hostile conditions at all the times. Moreover, in case if something suspicious is detected by the system, it must be able to take the necessary decisions and hence actions along with issuing alert messages for the human controllers. This robotic vehicle is designed for reconnaissance live update as well as surveillance under certain circumstances. Keyword: IoT Technology, Multi Sensor Robot, Surveillance, Wi-Fi, Live update.

Abstract: Today is an information age, and people of all ages use smartphones and social media to convey information. This information is not always reliable; sometimes false information is spread over social media. The proliferation of fake news is a major problem all around the world. Fake news is infiltrating human minds via social media. After reading the news articles on Facebook, WhatsApp, Instagram, Twitter, and other social media platforms, Sometimes these publications convey the inaccurate or incorrect message, which is referred to as fake news. This fake news is being a very big scam in which many people are being trapped. To solve this big issue, it’s important to develop a system called “Fake news detection system”. This fake news detection system detects the fake news by the prefilled data by various articles, from various sources. The earliest available systems uses some common methodology like Data Collection, Feature Extraction, Model Building and Model Evalution but only variations are seen in the use of techniques to solve the problem. This paper presents a Passive Aggressive Classifier Model with TfidfVectorizer Text Classification to address fake news. As per result obtained by proposed model it gives better accuracy than previous model used by researchers.

Keywords: Fake News Detection, Data Collection, Feature Extraction, Passive Aggressive Classifier, TfidfVectorizer

Abstract: A smart voting system using face recognition is a technique to overcome the traditional voting and EVM i.e Electronic Voting Machines. The system uses an Androidbased application to cast their votes from anywhere in the world. The face recognition technology increase the accuracy and security of the voting process. The proposed system would work as follows: voters should install the Android-based voting software and register themselves with their personal details and facial images. On the day of the election, voters should log in to the Android-based voting software and use their registered facial images for verification. Once verified, the voter can cast his vote. The proposed system uses facial recognition technology to reduce the fraud votes. The system also eliminates the manual verification of voters, it decreases the risk of human error and increasing the speed of the voting process.

Keywords: Deep learning, CNN, FaceNet Algorithm, Face Recognition, Smart online voting System.

Abstract: Digitalization enabled all economic opportunities while also perplexing the system with illegal activities. Credit cards are an example of a banking system advancement. The ease of use of credit cards enabled it to attract new users every day. Because of its popularity, the number of fake users, false transactions, and card theft has increased over the years. To puta stop to such illegal acts, fraud detection systems were created.The goal of our proposed paper is to determine whether the completed transaction is true or false. We used ML techniques such as logistic regression and random forest to extract the results. The Random Forest algorithm approach has been shown to provide an accurate estimate of generalization error. The Random Forest algorithm approach was discovered toprovide a good estimate of the generalization error, to be resistant to overfitting, and to be very stable. The obtained results are assessed based on their accuracy, specificity, and precision.

Keywords: credit card, fraud detection, logistic regression, random forest

Keywords: Plant disease, agricultural automation, computer vision, multilabel classification method, convolutional neural network (CNN) architectures

Abstract: Detecting and monitoring plant diseases are a crucial task in agriculture. The agricultural sector plays a vital role in the Indian economy, and early detection of crop diseases can improve both the quantity and quality of crops while reducing the time required for disease detection. This system for pepper plant leaf disease detection begins with data collection, which can be done through either surveying local agricultural land or collecting data from agricultural colleges. The collected images are then pre-processed to suppress unwanted distortions and enhance image features like contrast and size. Feature extraction is performed using the discrete wavelet transform, particularly the Haar wavelet compression, which samples the wavelet at discrete intervals. An artificial neural network classifier then classifies the image as healthy or unhealthy by utilizing the extracted image features. The classifier employs the back-propagation algorithm to achieve higher performance and accuracy.

Keywords: Artificial Neural Network (ANN), DWT2 (2-D Discrete Wavelet Transform), Image Processing, Pepper Plant

Abstract: One of the biggest issues facing the healthcare industry is chronic diseases. The global populace consumes a lot of unhealthy food. Generally speaking, doctors must thoroughly review the patient's records in order to diagnose the ailment. Sometimes it is difficult for doctors to treat patients effectively since the diagnosis is manual. Chronic disease patients are becoming more and more numerous every day. Therefore, environmental threat assessment is important. Currently, the digitization of healthcare is taking advantage of advances in medical care in hospitals. The traditional style lacks the knowledge development to monitor and analyze problems and views of traditional situations and has been replaced by the process of gaining better understanding from clinical data through the use of predictive analytics and fact. time machine readable tools. Reduce the size to include conditions like heart, stroke, diabetes, and cancer across multiple datasets using keywords selected in the research using machine learning penalty debt. Feature selection plays an important role in machine learning by selecting key features for live event detection.

Keywords: MachineLearning; sklearn; Randomforest; Linear regression.

Abstract: The dominant asset, Bitcoin, has a significant impact on blockchain technology. In project, proposed to correctly forecast the Bitcoin price while taking into account a number of factors that influence the Bitcoin value. In addition to learning about the best features related to Bitcoin price, our goal is to comprehend and identify everyday trends in the Bitcoin market. data set comprises of different elements that have been tracked daily over the course of each year in relation to the Bitcoin price and payment network. To forecast the closing price of the following day, factors including the opening price, highest price, lowest price, closing price, volume of Bitcoin, volume of other currencies, and weighted price were taken into account. Using the Scikit-Learn tools and the random forest model, predictive.

Keywords: Machine learning, Time series analysis, Sentiment analysis, Regression analysis, Deep learning, and other.

Abstract: TRANSCRIPTOR software can translate foreign languages into native languages; however, translation, language and punctuation errors may result in partial translations. To get an accurate translation, native speakers need to adjust the translation to capture the exact meaning using the verb and word of the sentence. Speech-to-speech translation is a tool designed to bridge the differences between people and foreigners when traveling in our country. This need stems from the inability of dictionary and human translation to meet our need for better communication. Our software does the same with video.

Keywords: Language Translation, Transcriptor, Speech to text, Subtitles.

Abstract: Air pollution is one of the major environmental problems affecting human health and ecosystems. Traditional air quality monitoring systems provide limited coverage and may not accurately reflect the actual air quality in a particular location. In this paper, a short survey of a smart air pollution detection monitoring system is studied that uses low-cost sensors, wireless communication, and cloud-based data analysis. The system provides users with real-time air quality information through a web interface and alerts users when air pollution levels exceed certain thresholds.

Abstract: Students can choose institutions or universities that fit their academic and career aspirations with the aid of a higher education recommendation system that uses the KNN algorithm. A machine learning technique called the KNN algorithm finds the K closest neighbours to a given data point based on a similarity metric. The algorithm in a recommendation system uses this similarity measure to identify the K institutions that are the most similar to a student's choices and suggests them as prospective possibilities. The KNN algorithm needs a dataset of colleges with information on their location, tuition costs, admission rate, student- faculty ratio, and programmes they offer in order to develop a recommendation system for higher education.The student's preferences must also be reflected in terms of these characteristics. The KNN method can then be used to discover the K universities that are closest to the student's preferences and offer them as potential options. The KNN method frequently uses the Euclidean distance as the similarity metric. We can determine the K universities that are closest to a student's choices by measuring the distance between each institution in the dataset and the student's preferences. These K universities may then be suggested to the student. Cross- validation or holdout validation techniques can be used to assess the performance of the recommendation system. In cross-validation, the dataset is divided into k-folds, the model is trained on k-1 folds, and it is then tested on the final fold. Holdout validation involves training the model on the training set, then testing it on the testing set after randomly partitioning the dataset into training and testing sets. In conclusion, a KNN-based recommendation system for higher education can help students choose colleges that will best suit their academic and professional objectives.

Keywords: Higher education, recommendation system, K-nearest neighbours (KNN) algorithm,machine learning.

Abstract: The development of a Music Recommendation System involved the utilization of the FER-2013 and Age, Gender (Facial Data) datasets. The system utilizes the CNN architecture, commonly employed for such purposes, to train three separate models: Emotion, Gender, and Age. To enhance the models' performance, additional layers are incorporated into the training phase. These models are subsequently employed as classifiers. To predict the user's mood, age, and gender, a snapshot of the user captured through the camera is forwarded to the trained models. Based on the outcomes of these classifiers, various playlists sourced from a database are suggested to the user. The goal is to create a functional and user-friendly environment for music selection. Once the playlists are proposed, the user can select their desired playlist and begin listening to the recommended music.

Keywords: Deep Learning, CNN, Emotion, Age, Gender, Music Recommendation System.

Abstract: Alzheimer’s Disease (AD) is very common neurological diseases these days. Alzheimer's disease (AD) is one of the most neurological disorders. One such condition that gradually deprives people of their memories and other crucial mental abilities and eventually results in dementia is Alzheimer's. To prevent any significant breakdown, it is essential to identify and treat it in its early stages. Although AD is exceedingly difficult to diagnose using conventional medical techniques, they employed multiple classifications on MRI scans. Imaging acquisition and pre-processing have been done to achieve better results. There have been many methods developed over the years to identify and cure brain disorders, but with the quick advancement of technology, this study has developed an idea to incorporate deep learning methods to identify and gauge a patient's brain status.

Keywords: Convolutional Neural Network (CNN), Densenet121, InceptionV3, Resnet50, VGG16, Deep Learning (DL), Kaggle ADNI Dataset.

Abstract: Radar is an object detection system which uses radio waves to determine the range, altitude, direction, or speed of objects. The radar dish or antenna transmits pulses of radio waves or microwaves which bounce off any object in their path. Arduino is a single-board microcontroller to make using electronics in multi disciplinary projects more accessible. This project aims at making a Radar that is efficient, cheaper and reflects all the possible techniques that a radar consists of. The proposed system "ultrasonic radar for the object detection distance and the speed measurement” employs an ultrasonic module that includes an ultrasonic transmitter and receiver. It operated by transmitting 40 kHz frequency pulse which is not audible to the human ear. Keywords: Radar, Antenna, Arduino, microcontroller

Abstract: As an AI language model, SYS-AI can be integrated into Flutter applications to provide users with a conversational experience. Using Flutter's user interface (UI) toolkit, developers can build custom chatbots and messaging interfaces that can leverage the power of SYS-AI to generate natural language responses to user inputs. With SYS-AI, Flutter applications can provide users with personalized and engaging conversations that mimic human-like interactions. Whether it's answering user queries, providing recommendations or assisting with tasks, SYS-AI can enhance the user experience and make Flutter apps more interactive and intuitive.

Keywords: Language Processing (NLP), Artificial Intelligence, Chatbot Development, Machine Learning.

Abstract: The popularity of capturing images has increased in recent years, as images contain a wealth of information that is essential to our daily lives. Although various tools are available to improve image quality, they are often used to falsify images, leading to the spread of misinformation. This has resulted in a significant increase in image forgeries, which is now a major concern. To address this, a decision fusion method is proposed in this project, which uses lightweight deep learning-based models for detecting image forgery. The proposed approach involves two phases that utilize pretrained and fine-tuned models, including SqueezeNet, MobileNetV2, and ShuffleNet, to extract features from images and detect image forgery. In the first phase, lightweight models are used to extract features from images without regularization, while in the second phase, fine-tuned models with fusion and regularization are employed to detect image forgery.

Keywords: Image Forgery, Deep Learning, Lightweight models, Convolutional Neural Networks (CNN)

Abstract: Traffic sign detection and classification is a crucial task in the field of autonomous driving, driver assistance systems, and traffic control. The objective is to propose a method that involves training a CNN on a large dataset of traffic sign images, which allows the network to learn the relevant features and patterns required for accurate detection and classification. Working on multiple datasets of standard benchmark and others helps to explore the difficulties and short comings of a CNN model proposed. Results are aimed to be helping in correct detection of a traffic sign and reducing the loss also using the GUI with the help of Tkinter.

Keywords: Convolutional Neural Network (CNN), Graphical user interface (GUI), Dataset, Tkinter.

Abstract: 3D printing has turned into a remarkable point in today's innovative exchange. Here, we will look at additive manufacturing or 3D printing. We will firstly characterize what we mean by this term and what is so noteworthy about it. We will dive a bit into the history. At that point, we should see about the procedure of 3D printing and the materials utilized as a part of the production of 3D printed objects. We might likewise see the focal points and burdens of 3D printing. We should watch the various applications it is being out to utilize today. At last, the future capability of this innovation is illustrated.

Keywords: 3D printing, 3D printers, polymers, Stereolithography, Additive manufacturing.

Abstract: Battery management systems (BMS) are used in electric vehicles to monitor and control the charging and discharging of rechargeable batteries, making operation more economical. The battery management system ensures that the battery remains safe and reliable and its performance is increased without it entering a harmful state. Various monitoring techniques are used to monitor the battery's condition, voltage, current, and ambient temperature. Various analogue/digital sensors with microcontrollers are used for monitoring. This paper deals with the state of charge, state of health, state of life and maximum capacity of a battery. By reviewing all these methods, future challenges and possible solutions can be identified. With the rapidly developing technology of smart grid and electric vehicles, battery has emerged as the most important energy storage device that attracts much attention. It is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable and cost-effective solution. The special features and requirements of the smart grid and electric vehicles, such as deep charge/discharge protection and accurate state of charge (SOC) and state of health (SOH) estimation, increase the need for a more efficient BMS. The BMS should include accurate algorithms for measuring and estimating the functional state of the battery while being equipped with advanced mechanisms to protect the battery from hazardous and inefficient operating conditions.

Keywords: BMS, SOC, SOH, Temperature.

Keywords: IoT, Rain sensor module, DC motor, ESP8266, Clothing stand.

Abstract: The proposed point Keylogger which is likewise called as keystroke logger is a product that tracks or logs the key struck on your console, regularly in a mystery way that you have no clue about that your activities are being observed. Most of the people tend to see only bad side of this particular software but it also has legitimate use. Aside from being utilized for vindictive purpose like gathering account data, Visa numbers, client names, passwords, and other private information, it can be used in office to check on your employees, at home to monitor your children’s activities and by law enforcement to examine and follow occurrences connected to the utilization of PCs. The project will be completely based on Python where I will make use of pynput module which is not a standard python module and needs to be installed. The software that I am going to build should monitor the keyboard movement and stores the output in a file. To elevate the project I will also add a feature where the logs will be directly sent to the e-mail.

Keywords: Security Analysis, Research.

Abstract: The Cloud computing system has a wide range of because of its flexibility and scalability method authentication mechanism and TKSE algorithm. The system also allows the owner of the data to set predefined keywords for their files that are uploaded into the cloud. However, data breaches and unauthorized access to cloud data are major concerns. Our system enables clients to access their data using a two method authentication and the user can find this data using a keyword search algorithm.

Keywords: Client side cryptography, Trustworthy keyword search encryption (TKSE), Cloud computing, secret key, Decryption key, Searchable symmetric encryption scheme (SSE), Two method authentication mechanism.

Abstract: The condition of the vascular network of the human eye is an important diagnostic factor in retinopathy. Its segmentation in fundus imaging is a nontrivial task due to the variable size of vessels, relatively low contrast, and potential presence of pathologies like microaneurysm and hemorrhages. The Project proposes the Retinal image analysis through efficient detection of vessels and exudates for retinal vasculature disorder analysis. It plays an important role in the detection of some diseases in their early stages, such as diabetes, which can be performed by comparison of the states of retinal blood vessels. Intrinsic characteristics of retinal images make the blood vessel detection process difficult. Here, we proposed a new algorithm to detect the retinal blood vessels effectively. The green channel will be selected for image analysis to extract vessels accurately. The  Daubechies wavelet transform is used to enhance the image contrast for effective vessel detection.  To increase the efficiency of the morphological operators by reconstruction, they were applied using multi-structure elements. A simple thresholding method along opening and closing indicates the remained ridges belonging to vessels. The experimental result proves that the blood vessels and exudates can be effectively detected by applying this method to the retinal images.

Keywords: Diabetic retinopathy, Pre-processing, Feature extraction, Classification, Discrete curvelet transform, Global contrast normalization, Digital image processing, Artificial neural network, Neural network classifier.

Abstract: An  timetable generator is a software tool that uses genetic algorithms to create an optimized schedule of events or activities within a specified timeframe. This tool is particularly useful for educational institutions, where it is necessary to schedule classes, lectures, exams, and other academic events in a way that maximizes student and teacher availability while minimizing conflicts and overlaps. The automatic timetable generator considers various parameters, such as the availability of teachers and classrooms, the duration and frequency of classes, and the preferences of students and faculty members, among others. The generated timetable is designed to be feasible and efficient, with minimal conflicts and maximum utilization of resources. The use of an automatic timetable generator saves time, reduces errors, and ensures a fair and equitable distribution of resources, thereby improving the overall quality of the educational experience.

Keywords: Genetic algorithm, Fitness score, Constraints, Timetable.

Abstract: The Placement Preparation App is a comprehensive tool designed to help students prepare for work placements. This app provides a variety of features, including aptitude tests, interview preparation materials, daily self-assessment tests, and technical skills to help students succeed in their job search. With a user-friendly interface and personalized recommendations, the web application offers a customized approach that meets the individual needs of each user. The placement preparation app aims to bridge the gap between job seekers and recruiters by giving students a platform to showcase their skills and connect with potential employers. Through this web application, students can boost their confidence, improve their skills and increase their chances of getting a job offer.

Keywords: work placements, aptitude tests, self-assessment, etc.

Abstract: A learning management system (LMS) is a software application that is designed to manage, deliver, and track educational courses and training programs. The primary purpose of an LMS is to facilitate learning by providing a platform for students to access course materials, communicate with instructors and peers, and complete assignments and assessments. The key features of an LMS typically include content creation and management tools, learner management and tracking tools, and communication and collaboration tools. . This paper aims to provide an overview of the design and implementation of a learning management system that is tailored to the needs of educational institutions. The LMS includes features such as course management, student tracking, assessment and grading, and communication tools. The system is scalable and can be customized to meet the needs of individual institutions, making it a valuable asset for both small and large organizations . The design of the LMS was informed by an analysis of existing systems, as well as input from educators and administrators. The implementation of the system was carried out using industry-standard technologies and best practices, with a focus on usability, security, and performance. The system was tested and evaluated by a group of educators and students, and feedback was incorporated to improve its functionality and user experience .In conclusion, the learning management system presented in this paper provides a comprehensive solution for managing educational courses and training programs. The system's features and design make it a valuable asset for educational institutions looking to improve their online learning capabilities.

Keywords: Learning Management  System (LMS),Educational technology, Online Learning ,Course Management, Student Tracking.

Abstract: The computation of longer-term share prices requires a strong algorithmic foundation for the complicated process of stock value prediction. Due to the structure of the market, stock prices are connected, making it challenging to estimate expenses. The suggested algorithm employs machine learning methods like a recurrent neural network called Long Short Term Memory to estimate the share price using market data. Weights are corrected for each data point using stochastic gradient descent during this process. In contrast to the stock price predictor algorithms that are now accessible, our system will produce accurate results. To drive the graphical results, the network is trained and assessed with a range of input data sizes.

Keywords: Stock Market, Long Short- Term Memory, Machine Learning, Artificial Neural Networks, National Stock Exchange

Abstract: This outline paper explores the usage of Convolutional Mind Associations (CNN) in the revelation and affirmation of covered fingerprints. Covered fingerprints address a tremendous test in the field of extraordinary finger impression affirmation, as ordinary procedures are much of the time ill-suited to perceive the particular fingerprints that are available. To address this test, researchers have gone to artificial intelligence estimations, and explicitly, CNNs. The survey paper gives a diagram of the current status of assessment on the usage of CNNs for recognizing and seeing covered fingerprints, including an examination of the methodologies and procedures used in various examinations. The outline also covers the hardships searched in including CNNs for remarkable finger impression affirmation, for instance, the necessity for a ton of planning data, the difficulty in getting extraordinary pictures of covered fingerprints, and the prerequisite for successful component extraction and matching calculations. What's more, the paper discusses the possible usages of CNN-based finger impression affirmation development, including policing, and ID, and perceives districts where further investigation is supposed to chip away at the precision and viability of CNN-based novel finger impression affirmation systems. As a rule, survey paper gives an intensive framework of the current status of assessment on the usage of CNNs for recognizing and seeing covered fingerprints, and elements the capacity of this development for a large number of utilizations.

Keywords: CNN, Fingerprint recognition, Overlapping fingerprints.

Abstract: The Vehicle Speed Detection and Notification System for College Campus using Video Processing is a prototype system designed to monitor and regulate vehicle speed within a college campus. The system uses video processing techniques to detect and track vehicles within the campus, and notifies the authorities if any vehicle is found to be exceeding the speed limit. The prototype system uses OpenCV library to extract video from the camera, and implements Haar Cascade Classifier algorithm for vehicle detection. The system also includes a notification system that alerts the authorities via SMS or email. The prototype system has been successfully implemented and tested, and has the potential to be used as an effective tool for regulating vehicle speed and ensuring safety within college campuses.

Keywords: Principal Component Analysis (PCA), Pytesseract Algorithm, Background Subtraction, Haarcascade classifier

Keywords: Healthcare, Fog Computing, Security, Framework, Advanced Encryption Standard (AES), Data Encryption Standard (DES), Secure Hash Algorithm (SHA), Encryption, Decryption, Convergent, Privilege.

Abstract: A project terminal, also known as a project deliverable, refers to the final output or result of a project. It is the tangible or intangible product, service, or outcome that a project team creates and delivers to the project sponsor or client. The project terminal serves as the basis for assessing project success and provides a means of measuring whether the project goals and objectives have been achieved. The importance of developing a clear and concise project terminal cannot be overstated as it guides the project team in their activities and helps to ensure that the project is completed within budget, on time, and to the satisfaction of the stakeholders.

Keywords: Timeline, Deadline, Schedule, Milestone, Task dependencies, etc.

Abstract: Due to the wide variety of writing styles, the recognition of handwritten characters, particularly in Kannada, is a challenging area of study. In order to convert the handwritten text into an electronic format, this work focuses on deciphering handwritten Kannada characters utilizing deep learning algorithms and optical character recognition (OCR). Deep learning methods like recurrent neural networks (RNNs) and convolutional neural networks are the most renowned and widely used methods for handwriting recognition (CNNs). The paper examines the key algorithms for identifying and categorizing handwritten characters as well as the numerous approaches utilized for deciphering handwritten material. Towards the conclusion, the accuracy offered by various systems is contrasted. In general, technological developments have made life simpler, and the expanding interest in handwritten recognition in computer science follows this trend.

Keywords: Image Processing, CNN, deep learning, handwritten text, and classification.

Keywords: Game engine, UX, Animation, Scripting, Graphics, 2d Model, Gamer, System.

Abstract: With The rise of social media platforms has led to an increase in cyberbullying, a form of bullying that takes place online. To combat this problem, a hybrid machine learning model is proposed to detect cyberbullying on the Twitter social media network. The model combines traditional machine learning algorithms such as Support Vector Machines (SVM) and Logistic Regression (LR). This model has the potential to be extended to other social media platforms and can be used by social media companies to improve their content moderation policies and practices. By identifying and removing cyberbullying content, social media companies can create a safer online environment for their users.

Keywords: Support Vector Machine (SVM), Logistic Regression (LR), Machine Learning (ML), Text Classification (TC), Natural Language Processing (NLP), Cyber Bullying (CB).

Abstract:  In recent years, the field of bio-acoustics has witnessed a remarkable expansion as researchers explore the acoustic signals produced by various organisms. While most studies have focused on animal vocalizations, this research delves into an unexplored realm of plant-generated sounds. This study investigates the synthesis of bio-acoustics from plants, aiming to uncover the potential auditory emissions of flora and understand their underlying mechanisms. Furthermore, this study explores the factors influencing plant bio-acoustics, such as environmental conditions, plant development stages, and external stimuli. The results of this research hold implications for several domains, including plant physiology, ecology, and agriculture. Understanding the bio-acoustics of plants can shed light on their communication systems, potential defense mechanisms, and stress responses. With the help of ECG module, Arduino UNO, audio amplifier we can get the acoustics from the plants. This acoustics can be used for yogic meditation to calm people and pets on modification. The findings may contribute to the development of novel non-invasive techniques for monitoring plant health, optimizing crop yield, and enhancing ecosystem management. In conclusion, this study pioneers the exploration of bio-acoustics from plants, revealing the existence of distinct sonic emissions specific to different plant species. By unraveling the underlying mechanisms and influences on plant-generated sounds, this research opens new avenues for understanding the sonic world of flora and harnessing this knowledge for various practical applications. Index Terms: Bio-acoustics, stimuli, communication, sonic emissions, Arduino UNO, Audio amplifier.

Abstract: The product is a web-based totally android utility that essentially pursuits at charity via donations which as entire programmed in Java. In this we have used predominant characteristic donate, sell, view holder and so on. A food sharing application is a platform designed to connect people and businesses with surplus meals to the ones in want of meals. The purpose of this application is to reduce meals waste whilst addressing food insecurity and starvation. Customers can submit to be had food items, and other customers can request or declare them. Usual, meals sharing utility goals to create an extra sustainable and equitable food device by using leveraging era to attach food assets with individuals who want them. Via its person-friendly interface and social functions, the meals sharing utility encourages individuals and businesses to come to be more aware about their meals waste habits and promotes sustainable practices. This app is designed to make it clean for users to percentage surplus meals with others in their community, whether it be meals that is approximately to expire, leftovers from a meal. This platform helps to reduce food waste and alleviate hunger by using selling the sharing of extra meals, at the same time as also fostering an experience of network and social responsibility.

Keywords: Android application, Surplus sharing, Food donation, Donor, Hunger relief, Community engagement, Logistics, Social responsibility.

Abstract: In today’s digital signal processing (DSP) world, there is often a need to convert signals between time and frequency domains. FAST Fourier transform (FFT) is a widely used and popular circuit design technique in the communication fields. It is a reduced form of discrete Fourier transform (DFT) in mathematics nature. For this reason, the fast Fourier transform (FFT) has become one of the most important algorithms in the field. The FFT has played a significant role in digital signal processing field, especially in the advanced communication systems, such as orthogonal frequency division multiplexing (OFDM) and asymmetric digital subscriber line. All these systems require that the FFT computation must be high throughput and low latency. Therefore, designing a high-performance FFT circuit is an efficient solution to the abovementioned problems. The proposed architecture is an efficient combined single-path delay commutator-feedback (SDC-SDF) radix-2 pipelined fast Fourier transform architecture, which includes log₂N−1 SDC stages and 1 SDF stage. The SDC processing engine is proposed to achieve 100% hardware resource utilization by sharing the common arithmetic resource in the time-multiplexed approach, including both adders and multipliers. Thus, the required number of complex multipliers is reduced to log₄N−0.5, compared with log₂N−1 for the other radix-2 SDC/SDF architectures. In addition, the proposed architecture requires roughly minimum number of complex adders log₂ N+1 and complex delay memory 2N+1.5log₂N−1.5. Standard FPGA Flow is adapted to implement this project. i.e., right from specification to bit file generation, which is going to be programmed on FPGA. The Work chosen for this project is to Implement Pipelined FFT Architecture using Verilog HD and implemented on the FPGA Spartan6.

Keywords: FFT, SDF, SDC, FPGA.

Abstract: Accident detection using computer vision and video surveillance has developed into a useful but challenging task. This research suggests the identification of traffic accidents. The suggested framework makes use of an effective centroid -based GMM algorithm for surveillance footage after accurately detecting objects using the axis bounding box technique. The suggested architecture offers a reliable way to get common road traffic CCTV surveillance footage to have a high Detection Rate and a low False Alarm Rate. Using the suggested dataset, this framework was tested under a variety of situations, including bright sunlight, poor visibility, rain, hail, and snow. This framework was shown to be efficient and opens the door for the creation of general-purpose real-time vehicle accident detection systems. Additionally, this project makes use of the Geopy module to record the real-time.

Keywords: Road Accidents, Intelligent Transportation System, Real Time Monitoring, Emergency Response, Gaussian Mixture Model (GMM) Algorithm.

Abstract: "Traversify" is a modular home automation system that utilizes the Telegram API and Arduino platform to provide users with a contemporary solution to the common struggles associated with traditional home automation systems. With Traversify, users can remotely control various devices and appliances in their homes and industries from any part of world, offering convenience, scalability, modularity to incorporate features according to user's need and security. The system's modularity enables customization and scalability to meet individual user needs, while its security features, such as the ability to send pictures for security purposes, enhance overall safety and peace of mind for users. The system's architecture, implementation, and functionalities are detailed, with a focus on evaluating its performance in terms of user experience, security, and energy efficiency. The use of Telegram API provides a reliable and secure communication channel between the user and the home automation system, eliminating the need for third- party subscriptions and extra SIM cards.

Keywords: SIM, Arduino and API

Abstract: In this review, a literature survey of printed Patch Antenna designs at various resonant frequencies is presented. Performance parameters such as gain, return loss and radiation pattern of the patch antenna are analysed. We try to attain higher gain and bandwidth than existing structures by suitably modifying the antenna structure.

Keywords: Microstrip Patch antenna (MSA), Return Loss, Radiation Pattern, Gain, 5G, 28GHz.

Abstract: Data transmissions over wireless channels are affected by attenuation, distortion, interference and noise, which affect the receiver’s ability to receive correct information. Convolution encoding with Viterbi decoding is a powerful method for forward error correction. Convolution encoders and Viterbi decoders play an important role in digital communication especially, when channel is noisy and introduces errors in transmitted signal. The use of re-transmission methods is not efficient and has large latency measure up to the rising speed and data rates of communication links, the need of new techniques arise here to be compatible with those systems. Convolution encoding with forward error correction Viterbi decoding is designed. A Viterbi decoder uses the Viterbi algorithm for decoding a bit stream that has been encoded using Forward error correction based on a Convolutional code. The maximum likelihood detection of a digital stream is possible by Viterbi algorithm. In this paper, we present a Convolutional encoder and Viterbi decoder with a constraint length of 7 and code rate of 1/2. Implementation parameters for the decoder have been determined through simulation and the decoder should be implemented on a Xilinx FPGA Kit. Verilog HDL language is used as a design entry.

Keywords: Convolutional encoder, veterbi algorithm, decoder, FEC

Abstract: Super pixel segmentation is an effective technique for detecting copy-move forgery, which is a type of image manipulation where a portion of an image is copied and pasted onto another area of the same image. This technique works by grouping neighboring pixels with similar properties into perceptually meaningful units called super pixels. These super pixels are used to identify regions of an image that have been manipulated by identifying identical clusters of pixels. Various techniques can be combined with super pixel segmentation to improve the accuracy of the detection process, such as feature extraction and machine learning algorithms. The use of super pixel segmentation for copy-move forgery detection simplifies the image analysis process, making it easier to detect duplicate regions in the image. As image manipulation becomes increasingly prevalent, the development of new and innovative techniques like super pixel segmentation will become increasingly important for ensuring the integrity of digital images.  Index Terms - Super pixel segmentation, copy-move forgery, image manipulation, identical clusters of pixels, feature extraction, machine learning, accuracy, detection process, image analysis, digital images.

Keywords: Face recognition system for educational institutions that uses the Convolutional Neural Network (CNN)algorithm, deep learning, student dataset, Gray scale, Haar cascade, data registration.

Abstract: In this digital age, social networking platforms have become an integral part of our daily lives. However, there is a growing concern over the lack of privacy and security on existing platforms. This has led to the development of a new social networking platform that focuses on enhancing user privacy and security. This platform includes Private Reactions features to provide users with more control over their interactions. Additionally, the Personal followers/following list feature helps prevent digital stalking and harassment. The introduction of "Ghost mode" provides users with an extra layer of privacy and control over their profile. By incorporating these features, the platform aims to prevent cyberbullying and digital blackmail, creating a safer and more user-friendly environment for social networking.

Keywords: Social networking, security, cyberbully, cyberharassment, digital blackmail, private liking and commenting, personal followers and following lists, ghost account mode

Abstract: Many things have been altered throughout the period of advancement. Every industry, including those in the mechanical and electronic fields, has been embraced by internet and computer technology. Internet of things is one of the most practical and helpful aspects of technology. When we think of convenience, we envision scenarios in which we would work less and accomplish more. We can perform multiple tasks at once when we multitask. The Internet of Things is also concerned with these goals. The development of the important technology known as the internet of things has been facilitated by the support of coding along with hardware devices. The term "Internet of things" refers to the networked interconnection of smart devices. It develops a clever environment for comfort, security, and conservation. The Internet of Things may enhance people's quality of life. Due to the many advantages it offers, this field is used in almost every sector, including healthcare, agriculture, transportation, household goods, and industry. In this essay, we'll talk about the fundamentals of the internet of things, along with some common gadgets and applications.

Keywords: IoT, Sensors, Actuator, Controller, Processor, Devices.

Abstract: The evaluation of scripts is a crucial part of the education system that requires precision and efficiency. However, the traditional evaluation process often involves manual labour and is prone to errors, leading to delayed results and inconsistencies. This paper presents the development of a Digital Evaluation system using the Django Framework, which offers a modern and efficient solution to the evaluation process. The system allows staff to scan and upload scripts, which are then distributed to evaluators according to the subject code. Evaluators can then evaluate the scripts and upload the marks to the database. The system enables the department to view student results, including high and low scorers, and identify areas of improvement. The implementation of the Digital Evaluation system using Django Framework provides a customizable and scalable solution to simplify and enhance the evaluation process. The paper discusses the system architecture, implementation process, features, and benefits of the Digital Evaluation system. Overall, the Digital Evaluation system offers a more accurate, efficient, and customizable solution to the evaluation process, paving the way for modernizing the education system.

Keywords: Digital Evaluation, Staff, Evaluator, Exam Controller.

Keywords: Assistant, Experience, Intelligent, Potential

Abstract: Many major grain-producing nations have implemented steps to limit their grain exports as COVID-19 has expanded globally; food security has sparked significant worry from several stakeholders. One of the most crucial concerns facing all nations is how to increase grain output. Crop infections, however, are a challenging issue for many farmers, thus it's critical to understand the severity of crop diseases promptly and properly to support staff in taking additional intervention steps to reduce plants being further affected. This paper proposed a hybrid deep learning model that combines the benefits of deep residual networks and dense networks to identify tomato leaf disease. This model can reduce the number of training process parameters to increase calculation accuracy and improve the gradients and information flow. Since the original RDN model was developed for image super-resolution, we must modify the input image characteristics and hyperparameters to reorganize the network architecture for classification tasks. On the Tomato test dataset in the AI Challenger 2018 datasets, experimental findings demonstrate that this model can obtain a top-1 average identification accuracy of 95%, confirming its good performance. In terms of crop leaf recognition, the reconstructed residual dense network model can outperform the majority of the state-of-the-art models while using significantly less computing power. Index Terms: Agricultural artificial intelligence; tomato leaf diseases; residual dense network; identification of leaf diseases

Abstract: Any large-scale data sharing system needs this quality more than others because if a user accidentally discloses sensitive information, the owner of the data will find it harder to keep the information secure. For data owners, sharing their data on servers or in the cloud presents many difficulties. These methods are crucial for managing keys shared by the data owner. The trustworthy authority will be introduced in this article in order to authenticate users who have access to cloud data. The trustworthy authority generates the key using the SHA algorithm, and both the owner and the user will have access to it. The trusted authority module computes a hash value using the MD-5 method after receiving an AES-encrypted file from the data owner. a file is sent to the CSP module by a trusted authority for cloud storage.

Keywords: SHA algorithm, AES algorithm, MD-5 algorithm.

Abstract: The Multilingual YouTube Transcript Summarizer project utilizes machine learning and natural language processing techniques to provide an automated summary of the transcripts of YouTube videos. The project involves extracting the text from the video transcripts, analyzing the language patterns, and using algorithms to generate a concise summary of the content. This technology can assist users in quickly identifying key points and important information within lengthy videos. The project utilizes machine learning techniques to continually improve the quality and accuracy of the summaries, ensuring that they are relevant and useful for viewers. Natural language processing is also utilized to identify important keywords and phrases within the text and to analyze the tone and sentiment of the content. The YouTube Transcript Summarizer project represents an exciting advancement in the field of artificial intelligence, offering a powerful tool for anyone looking to save time and streamline their video-watching experience.

Keywords: Natural language processing (NLP), Machine learning, Text mining, Language detection, Keyword extraction, Speech recognition, Text classification

Abstract: Cloud computing is the on-demand delivery of computer system resources primarily data storage and processing power without direct, active user oversight. The Cloud is a collection of diverse materials. Cloud computing's handling of storage has made load balancing possible. The practice of efficiently distributing the load among the servers such that no server is overcrowded or under loaded is known as load balancing. This is accomplished by effectively and successfully splitting the task using the Enhanced Weighted Round Robin. This project's main goal is to reduce response time while enhancing performance by USING GAA algorithm. Using Genetic algorithm for providing expected service result to the user as well as using Any Colony algorithm for efficient resource managing that helps to reduce the response time. Mainly resource allocation are theoritically provides best result but in practical user suffers with bad experience. For that using Analytical algorithm, it helps to analyze the data from the user request and make a decision to process the data in the analytical mode. Finally, efficient resource allocation in data center can be calculated and analyzed by using the combining algorithm of Genetic, Ant Colony and Analytical.  

Keywords: Service And Vm Scheduling , Analysis , Static load Balancing , Optimal Static Load Balancing Algorithms , Quality of Services, Genetic Algorithm , Ant Colony Optimization , Analytical Algorithm.

Abstract: Due to the many accidents in our diary life, we are IMPLEMENTION OF ANTIGLARE HIGH BEAM AND BENDING LIGHTS FOR VEHICLES .to improper use of high beams can cause glare interference to oncoming drivers or pedestrian. The accidents can be avoided by incorporating Steering Control Headlight Mechanism.

Keywords: Sensors, high beam, bending lights.

Abstract: Wild animal intrusion has always been a persisting problem. A lethal conflict is below way among India’s developing population and its wildlife limited to ever-shrinking forests and grasslands. In forest and agricultural zones, human animal conflict is quite an issue where enormous amounts of resources are lost and human life is threatened. The reason behind animals attacking humans cannot be confined to a single cause. Certain animal attacks happen due to humans provoking them and others are purely based on instinct which is often the case and for which nothing can be done. There are no specific reasons for animals attacking humans based on instincts. In any way, animal attacks are daunting. Apart from posing a threat to human life, Crop damage caused by animal attacks resulting in reducing the crop yield is also yet another consequence. Hence their activity must be monitored continuously in order to take action in case of animal intrusion in attack prone areas. Due to the diverse nature of movement and physical sizes of wild animals, it is a challenging task to track these animals or perform surveillance. In order to tackle the issue, we are developing a system to monitor these areas that will detect the intrusion of wild animals using image processing where classification is performed using Deep learning algorithms. Suitable action is taken based on the type of intruder and an alert is sent if the type matches the predefined wild animal datasets.

Keywords: Intrusion alert, Faster Regional Convolutional Neural Networks, Attack prone areas, Wildlife Datasets, Deep learning

Abstract: As we can see, the trend of online shopping has evolved over the past two decades into a practical choice for everyone of us. Due to the expanding demand and desire for online shopping and online enterprises, Businesspeople must constantly rely on computer science and related technology to understand what the customer wants. Yet, because the number of consumers is expanding quickly and on a larger scale online, it is challenging for interested parties to fully comprehend the reviews they require to evaluate a product. Moreover, some product reviews are fake. Consumers and product providers that seek to meet the demands of the client encounter obstacles as a result of this.  The quantity of client reviews for the goods increases quickly as e-commerce expands and gains popularity every day. A well-liked product may have hundreds of reviews, perhaps thousands. Because of this, it is challenging for a potential customer to read them and decide whether or not to acquire the items. In this research, a method is implemented that makes use of data mining to analyze real product evaluations submitted by real consumers, notifies the creators and other consumers of the positive or negative review, and blacklists bogus accounts. Moreover, there are a few bogus product evaluations from time to time. Consumers and product manufacturers that make an effort to understand the demands of the customer both encounter difficulties as a result. Finally, after they have reviewed the product themselves, the comment will be automatically checked to see if it is positive or negative. Fake accounts will also be blocked and prevented from accessing further. Based on experimental research and surveys, this review monitoring technique was found to be successful and efficient.

Keywords:  online shopping, client needs, product reviews, false reviews, e-commerce, data mining, authentication, summary of reviews, positive/negative comments, fake accounts, review monitoring, successful and efficient.

Abstract: In India, where one in every three houses owns a two-wheeler, around 15 million two-wheelers are sold each year. Each year, the nation manufactures 20 million two-wheelers. A severely underinflated tyre may experience mechanical and thermal stress as a result of overheating, which can quickly result in the tyre blowing out. Failures of this kind may lead to risks and accidents that put everyone nearby at danger in addition to the rider. According to average country estimates, under-inflated tyres lead to tread separation and tyre failure, which result in 40,000 accidents, 33,000 injuries, and over 700 fatalities each year. The population of India, however, may cause these numbers to increase because more individuals own 2-wheelers, have less time to personally check, and are unable to get their autos regularly inspected at a repair facility. The aforementioned problems will happen more frequently if the riders are unaware of them. The goal of this project is to develop and build a direct tyre pressure monitoring system (TPMS), which measures tyre pressure directly using a pressure sensor. When the TPMS notices a drop in tyre pressure, the rider does not have to exit the vehicle and manually pump air into the tyres because the TPMS and compressor unit are working together to supply the air to the tyre. The device receives power from a dynamo or a backup battery. The major components must be calibrated to guarantee consistency and accuracy in reporting the pressure and giving the tyre enough air. This prototype is a potential product for usage in the real world, despite the many difficulties and limitations.  

Keywords: TPMS, compressor, Tire pressure, two-wheelers.

Abstract: Image description generator using Deep Learning can create an image's content using properly constructed, meaningful English sentences. The user's camera or mobile phone is continuously used to capture images in real-time. Our models extract features from an image using a convolutional neural network (CNN). To create a reliable image description in English, these Features Are Provided to A Recurrent Neural Network (RNN) Or A Long Short-Term Memory (LSTM) Network. We Use A CNN To Extract Features from The Image. CNNs are the state-of-the-art methods for object recognition and detection and have been used and studied for a variety of image tasks. In more detail, we extract features from the Fc7 Layer of the VGG-16 Network that has been trained on ImageNet and is well suited for object detection for all input images. Due to computational limitations in LSTM, we first obtain a 4096-dimensional image feature vector and then reduce it using principal component analysis (PCA) to a 512-dimensional image feature vector. These characteristics are fed into the LSTM network to produce a description of the image in accurate English, which might then be converted to audio using text-to-speech technology. Keywords- Caption Generator, Feature Extraction, LSTM, Neural Network, Object Detection

Abstract: An analogue data logger (also known as a data recorder or logger) is an electrical device that captures data over time or in relation to location using either internal instruments and sensors or external instruments and sensors. They partially (but not entirely) depend on a digital processor or computer. They are generally small, battery-powered, portable devices with a microprocessor, internal memory for data storage, and sensors. Some devices can function independently and have a local interface (keypad, LCD). Some data recorders employ software to activate the device, view, and analyse the recorded data when connected to a computer. There are many various types of data loggers, from general-purpose devices used for a wide range of measurement applications to highly specialist devices used for only one kind of environment or application. Although programmability is often found in general-purpose types, many still operate as static machines with few or no customizable options. Electronic data loggers have replaced chart recorders in many applications. The ability of data loggers to automatically and continually collect data is one of its key benefits. In order to measure and record data, data loggers are typically turned on, deployed, and left alone for the length of the monitoring period. This makes it possible to monitor environmental factors like air temperature and relative humidity in order to provide a full and accurate picture.

Keywords: Data Logger, Microprocessor, Instrumentation, Measurement, Signal Processing, Programmability, Sensors.

Abstract: The goal of this project is to create an accident prevention system for hilly regions to alert and prevent accidents by making use of the Arduino Uno as the primary design component. The current leading cause of death in developing nations is vehicle accident. Some of the world's dangerous routes include mountainous and winding. Every year more than 1.5% increase in road accident and it is approximately more than 6 lakh road accidents in India, for every one minute one road accident and for every 4 minutes one death due to road accident. India is losing very huge youth as the maximum death age group are from 16 to 30 years European countries. There will be curvy, narrow roads in the mountainous areas. The person driving most of the times cannot see the vehicle approaching from other side in such circumstances also the opposite side may lead to a cliff. Each year, thousands of lives are lost as a result of this issue.  

Keywords: Curve roads, Accident Prevention, GPS and GSM Module, Arduino UNO and Nano

Keywords: Diabetic retinopathy (DR), Colour fundus images, Convolutional neural network (CNN), graphics processor unit (GPU), Kaggle dataset.

Abstract: Accurate classification of arrhythmias is critical for timely and effective treatment. In this study, we propose a novel approach for arrhythmia classification using 2D spectral images generated from 1D electrocardiogram (ECG) signals. We utilized deep learning algorithms, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to classify ECG signals into various types of arrhythmias. The proposed approach was evaluated on a large ECG dataset and achieved a high accuracy rate of 99.16%. Furthermore, we employed cloud computing to enable faster and more efficient model training and validation. Our approach has the potential to improve the accuracy and speed of arrhythmia classification and enable remote diagnosis and monitoring of patients using cloud-based platforms. Keywords: Cloud computing, deep learning, arrhythmia classification, ECG, spectral images.

Abstract: In modern society, the main issue with fuel stations is the lengthy wait times for fill-ups, even though the money handling process is completed fast thanks to the project's implementation. The petrol station now offers UPI ID for use exclusively in transactions. Everything is digital now. Nearly all petrol pumps in many current systems feature a controlling device to manage the electrical pump, operate the display, measure the flow, and then turn OFF the electrical pump. However, a person is still needed to collect the money, and there is always a chance for human error. In the proposed automated fuel pump system, we use UPI QR Code to obtain fuel at various petrol stations owned by various petroleum corporations across the nation. We only need to scan the QR Code and make payment each time we use the petrol dispenser to fill up the tank. The GSM module then reads the message and takes the appropriate action in accordance with the requests of the customer. By removing the involvement of people, this computerized petrol pump system also offers security to customers when they fill up at petrol stations.

Keywords: GSM, UPI ID, QR Code

Abstract: Gun violence has become a first-rate motive ultra-modern misery in the present society. the dearth state -of-the-art right mechanisms to stumble on and become aware of guns in advance outcomes within the increase modern -day the impact caused by gun-related violence. This idea paper offers a look at for concealed weapon detection in IR photographs using picture Processing and open CV and CNN. The proposed device will perform the fusion today's IR photos with corresponding RGB pics accompanied by open cv detection models. Protection and safety is a massive situation for today’s modern-day world. For a rustic to be economically robust, it ought to make certain a safe and comfy surroundings for investors and travellers . Having stated that, Closed Circuit television (CCTV) cameras are getting used for surveillance and to display sports i.e. robberies however those cameras still require human supervision and intervention.  Index Terms :  Gun detection, deep studying, item detection, artificial intelligence, laptop imaginative and prescient.

Abstract: A new era in computing history known as the "Internet of Things" (IoT) is about to begin. Machine to machine, machine to infrastructure, machine to environment, Internet of Everything, Internet of Intelligent Things, or the  development of intelligent methods—whatever name you give it, it is and has huge potential. Rain and landslide expertise in the field. weather analytics techniques can provide valuable insights into the potential for rain and early warning of these events can help to minimize their negative impacts and reduce the risks associated with infrastructure planning and maintenance, land use planning, and agriculture and forestry management.

Abstract: As engineering is constantly changing and has a huge impact  on the various aspects of our lives, it has become very much  important for each and every individuals to get access to quality engineering education in the in native or regional language. Where many huge universities and top class institutions offer engineering courses in English, not everyone who completed their schooling in regional language may be fluent in reading and writing in English or feel comfortable learning in it. This is where a portal to learn engineering in Kannada language can be most valuable. Such a portal would provide engineering education in Kannada languages, making it more accessible and more easier to understand for those who are not proficient in English. This portal could offer a variety of engineering courses , including mechanical engineering, electrical engineering, civil engineering, and more, and also provide necessary resources for the courses to the students  in Kannada language. In addition to language accessibility, the portal could also address the issue of engineering education being limited to certain geographic regions. By providing education in Kannada languages, the portal could reach the students who leave in rural or remote areas who may not have access to traditional engineering programs. Overall, a portal to learn engineering in Kannada language has the potential to democratize access to engineering education, empower individual to have a great  engineering careers, and contribute to the overall growth and development in engineering field.

Keywords: Quality Engineering Education, Regional Language, Kannada Language, Traditional Engineering Programs, engineering careers.

Abstract: In modern society, Many approaches, including the implementation of monitoring systems, have been undertaken to stop the abnormal human actions. If the monitoring systems can detect unusual human activity automatically and send out alarm or warning signals, that will be quite significant. The first step is for the algorithm to recognize whether there are any people in a frame of footage. Then, it's necessary to remove the frames that are likely to include abnormal human behavior. At this time, the useless frames should be removed. When a human exhibits abnormal behavior, the trained model identifies it and distinct photos of those frames are kept. The ability to identify faces in these pictures has been improved. Here is the requirement to develop an automated security system that identifies the abnormal human activity in real-time so one can immediately take action on it. It is a very lengthy process to get abnormal human activity from lengthy surveillance videos so it will compress the video before passing it throw the activity recognition system so that system can first retain the objects of interest and then it can be passed throw the model. Utilizing just CNN (Convolutional Neural Network) is less accurate and consumes a lot of computing time. As a result, MobileNet, a pre-trained model, is used as the foundation for developing the complete model and offers improved accuracy. Telebot uses the Telegram app to send an alarm message to the relevant authorities.

Keywords: GSM, UPI ID,QR Code

Abstract: Farming is the most common occupation in India. As agriculture is incredibly important to feed the nation that has huge population. Nowadays, when it comes to farming, the sophisticated methods and automated machinery that are taking the world to new heights have lagged. Either a lack of knowledge about sophisticated tools or their unavailability contributes to the poverty in farming. Our Aim is to make a website by offering a variety of agriculture-related information on its website, BHARAT-AGRI has been established to improve farming. It will help the farmers to improve their productivity and profitability. Bharat-Agri is a modern farmer updated web-based application which will be helping farmers to get connected to an Agriculture center expert directly. Our application can help to make farming practices much more comfortable, predictable, confident, and profitable.

Keywords: Internet of Things (IOT), Smart Agriculture using IOT, ESP32 board, Soil Moisture Sensor, Water level Sensor.

Abstract: It has an impact on everyone's health, which is why mental illness should be prioritized in the healthcare industry. However, it appears that this field is developing at a somewhat slow pace. AI (Artificial-Intelligence) technologies have recently received a lot of attention in a variety of fields, including mental health. Advanced AI approaches and machine learning algorithms have made it possible to provide personalized care that primarily focuses on providing emotional support tailored to a specific individual. We explore the possibility of using large language models like OpenAI’s GPT3 and Facebook’s Llama and Stanford’s Alpaca to provide an effective conversational partner to people suffering with such mental health conditions where it may be helpful, such as depression and anxiety disorders. We compare the performance of the chatbots based on their responses to questions from counselchat.com dataset of therapist responses, and use the GPT4-davinci, the largest GPT4 model, as a judge to evaluate the quality of responses.

Keywords: AI (Artificial intelligence), LLMs (Large Language Models), Fine-tuning, chatbot, depression, anxiety, mental health.

Abstract: According to the recent report published by WHO, Cardiovascular diseases are the leading cause of death globally, taking an estimated 17.9 million lives each year. CVDs are a group of disorders of the heart and blood vessels and includes rheumatic heart disease, cerebrovascular disease, coronary heart disease and other conditions. The basic cause of CVD death is due to heart attacks and strokes and one third of these deaths occur prematurely in folks under 70 years of age. With rapid increase in population, pollution and frequently changing lifestyle of a human being, it becomes a challenge to diagnose a disease and provide the relevant ministration at the right time. With the help of advancements in the technological tools and techniques, machine learning plays a vital role in training and testing the abundant data in the medical field and takes less time in predicting the same with foremost correct and reliable formulas. In this paper we have surveyed the various research papers published in this domain in the recent years and formulated a table which includes various techniques and their corresponding algorithms used with their level accuracy, pros and limitations and also studied the future scope so as to propose a model in the near future which predicts the heart disease with high degree of accuracy and results in robust way of saving the lives at large.

Keywords: KNN, SVM, DECISION TREE, LOGISTIC REGRESSION

Keywords: Traffic, open CV, Perdition.

Abstract: Visually challenged people frequently have difficulty with simple daily task like walking and travelling. They always require some help. Most of them use wooden sticks for assistance. However it has its own drawback. With the evolution of technology, Smart devices such as watch, eye wear and other items has made daily like easier. This application discusses about the smart goggle for people who visually impaired. Smart goggle provides support by assisting with object detection. We employ the deep learning algorithm YOLO V3 to identify the type of obstacle which uses the environment’s obstacle as a type of data set where environment obstacle is detected through beep sound. V oice assistance is available so that the user can comprehend the type of difficulty. The purpose of this application to provide the user speech based interface that allows them to transmit through headphones, earphones etc. Keywords: SmartGoggle, DeepLearning, YOLO V3,wooden stick, object detection.

Abstract: The sophistication of phishing assaults is rising, making it challenging to identify them using conventional means. Consequently, there will be a growing need for more advanced techniques to recognise and thwart such attacks. We introduce a hybrid deep learning strategy for phishing attack detection in this research. The proposed method of phishing website detection can be done by combining convolutional neural networks (CNN) and recurrent neural networks (RNN), two alternative deep learning models. The RNN is used to identify temporal dependencies in the data, while features have been determined from the unprocessed information using CNN. The hybrid model is highly accurate at identifying phishing assaults since it is trained on a vast dataset of authentic and phishing websites. We demonstrate that the suggested algorithm outperforms leading-edge methods by comparing its performance to those. Overall, our suggested method offers a reliable defence against phishing assaults and can be applied to increase the security of online systems.

Keywords: Legitimate, Phishing, Cyber Security, Deep learning, Feature Extraction, Websites, CNN, RNN.

Abstract: Advancements in wearable and smart textiles have revolutionized the way we interact with technology. Smart textiles are fabrics that can sense and respond to external stimuli, such as changes in temperature or pressure, while wearable technology includes devices that can be worn on the body to monitor various physiological parameters, such as heart rate, body temperature, and activity levels. These technologies are made possible by the integration of advanced sensors, microcontrollers, and wireless communication technologies into fabrics and clothing. Other important components include energy harvesting and storage systems, which allow these devices to function without the need for external power sources. Smart textiles and wearable technology have a wide range of applications in fields such as healthcare, sports, fashion, and entertainment. They have the potential to improve health outcomes, enhance athletic performance, and create new forms of interactive entertainment. Overall, the rapid development of wearable and smart textiles is a promising area of research that holds enormous potential for the future.

Keywords: Smart Textile Jacket, E-textiles, Fabrication, Sensors.

Abstract: Augmented Reality (AR) and the Internet Of Things (IoT) are ubiquitous technologies. Augmented Reality is a sub-domain of Mixed reality. Placing the virtual object in a real-time environment is called Augmented Reality. The Internet Of Things describes the network of physical objects that are embedded with sensors, software, and other technologies for connecting and sharing data with other devices and systems over the Internet. In the IoT part, we have used Blynk Cloud to create an On/Off button to control the home appliances in the dashboard. Then Blynk provides the Authentication token. The Authentication token uses to access the buttons we created in the Blynk Cloud and upload the code in the ESP32 WIFI module. After successfully uploading the code, then ESP32 is connected with the relay and home appliance, and by clicking the On button the appliances will On, and by clicking Off the appliances will turn Off. In the AR part, we used Unity to create a virtual button. Import the target images in Unity using the Vuforia engine. Then we placed the On/Off button on the target image and scan the target image using the mobile camera the button image will appear on the mobile screen. After that using the authentication token, pin, and value of the button in the Blynk Cloud we generated the URL. V0 and V1 are pin and value 0 for Off and 1 for On. Copy the URL and paste the URL in the dialog box in the Unity hub. Then build the application for Android using Unity. Install the application and scan the target images and the created virtual button will display on the mobile screen touching the virtual button in the target image we On/Off the home appliances. 

Abstract: In this report we get to learn the existing and the new developing methods of stock market prediction. To understand this, we learn about three different approaches: Fundamental analysis, Technical Analysis, and the application of Machine Learning. We find evidence in support of the weak form of the Efficient Market Hypothesis, that the useful information is not present in the historic price but out of sample data may be having an event or result. We show that Fundamental Analysis and Machine Learning can be used as a guide to affect the investor’s decisions. We demonstrate that thereis common problem in Technical Analysis methodology and show that it produces limited useful information. As we get various information based on it, development of algorithmic trading programs areto be done and simulated using Quantopian. Technical

Keywords: Stock Prediction, Data Analysis, Natural Language Processing, Machine Learning.

Abstract: Social media platforms have become a crucial part of our daily lives and play significant roles in various aspects such as business, entertainment, marketing, education, media, and communication. Among these platforms, YouTube has gained massive popularity as the most widely used platform for sharing videos due to its unique behavior. The platform allows anyone to create an account and upload videos of their choice, which can be viewed by millions of people. This has become a trend in the entertainment industry, making it easy for videos to reach users and gain popularity online. However, not all YouTube videos become popular, and many channel owners take various actions to make their videos popular. This research study uses sentiment analysis and feature extraction methods to derive the set of features required to consider in the development of YouTube videos. By analyzing user comments, the study aims to discover the most important trending videos related to user video types and the most trending videos that users will want to see. The study uses machine learning methods to analyze the trending features and identify key recommendations for the users. The results of the study will enable YouTubers to create videos that resonate with their audience and increase their chances of being popular. The study on YouTube trending videos and Support Vector Machine (SVM) algorithm has revealed the importance of views, likes, and dislikes in determining a video's trend. The SVM algorithm uses these factors to identify and predict which videos will become popular on the platform. This research study provides recommendations to YouTubers on how to create videos that can become trending by analyzing user comments, identifying their requirements, and using machine learning methods to derive the necessary features.

Keywords: KNN (K-Nearest Neighbors), SVM (Support Vector Machine), HDFS (Hadoop Distributed File System), CNN (Convolutional Neural Network), Feature Extraction methods, Machine Learning, MLP (Multi-Layer Perception), popularity

Abstract: The monitoring of sleep quality and the transmission of alarm signals in accordance with the condition and the acute disease fall under the purview of fundamental sleep research and disease outbreak forecasting. The system has monitoring and analysis features.the physiological features of the sleeper pulse, the embedded A computer can determine whether a sleeper has an acute illness (such as heart disease, cerebral haemorrhage, etc.). If so, the wireless warning signal is sent by the wrist pulse monitoring gadget. When the alarm is received by the bedside wireless receiver, it can send an alert sound or call. The warning sound can specifically alert local musicians to the sound of the phone alarm can notify the appropriate personnel and issue an alert using the predetermined phone number.let the 120 emergency centre know.At the same time, the bedside wireless remote devices open the door to wait for the arrival of emergency personnel.The system can respond when sudden acute illnesses strike at night.efficiently address the patient's urgent medical needs and establish the prerequisites for the patient's quick treatment.  

Keywords: Remote alarm; wristband;sleep monitoring ;Emergency; embedded system; pulse  monitoring Treatment.

Abstract: Conversing to a person with hearing disability is always a major challenge. Sign language has indelibly become the ultimate panacea and is a very powerful tool for individuals with hearing and speech disability to communicate their feelings and opinions to the world. It makes the integration process between them and others smooth and less complex. In this study, the user must be able to capture images of the hand gesture using web camera and the system shall predict and display the name of the captured image.  

Keywords: Sign Language, ASL, Hearing disability, Convolutional Neural Network (CNN), Computer Vision, Machine Learning, Gesture recognition, Sign language recognition, Hue Saturation Value algorithm.

Abstract: This study proposes a digital solution to address barriers to access to health services faced by immigrant communities, particularly regarding childhood vaccinations. The proposed tool, a mobile app/web interface, facilitates seamless vaccination processes by adding features such as seat reservations and personalized vaccination schedules. The goal of the initiative is to increase vaccination, strengthen children's immunity and improve the general health indicators of migrants through cooperation with local health providers and extensive information campaigns. Key to its success is the integration of culturally sensitive design elements and active community participation, ensuring relevance and effectiveness. Addressing language, information, and logistical challenges, this digital tool aims to close the gap in access to health care and promote equitable health outcomes for immigrant children. For this, both the system administrator and the user interface are created, and after reserving a place, a text message is also created for the user. This digital tool aims to bridge the gap in healthcare access by navigating language, information and logistical challenges. Cite: Dr. R. Nagarajan, Mr.T.T MELWIN, "ENHANCING CHILD IMMUNITY IN MIGRANT COMMUNITIES THROUGH DIGITAL TOOLS", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 3, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.133145.